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reporting services justificar texto

SQL Server Reporting Services (SSRS): How to Justify Text (Part 2)

Left, Right, and Center. Those are the only options right? That might be how SSRS views the world, but nope...

reporting services justificar texto

Full justification basically just means that both the left and the right sides of the text end at exactly the same place on the page, regardless of the line length. Word does it. Publisher does it. Even HTML and CSS can do it. (You'll notice this is the only entry on the Phidiax blog that is full justified)

Unfortunately for those using SSRS to render extended text blocks from a database, SSRS just can't do it. At least not out of the box. Here's where some Googling (or Binging depending on your search engine preference), some language conversion, and some SSRS knowledge can come in handy to make all your text justification dreams come true.

There are two ways we can accomplish this (well, without having to buy custom SSRS components or switch to Crystal Reports). I'll cover them both... the best looking way ( here in part 1), and the "poor man's" justification using added spaces in this entry. This method  is provided solely in the event that your user base wants the rendered result to still be "text." It is not as accurate, rather gives the "feeling" of justified text. It leaves you at the mercy of the font's implementation of the Unicode "hair space" character and how well that evenly divides into the amount of required "empty space" between words. This was developed because I had a client in just this situation: wanting justified text without converting to an image in the resulting rendered document. Admittedly, keeping it as text provides superior quality when printing or exporting to PDF, especially in limited memory environments.

Adding Hair Spacing To Text

So to justify text, we basically need to divide the text into paragraphs by carriage returns, then by words with spaces, and measure the size of how each word will render in the selected font to determine how many words will fit on each line, and as a result, how many Unicode "hair space" characters are needed between each word in that line to present that line as justified. As each line is calculated, it has the regular space characters replaced with hair space characters. Once the space "goes over" expected space, additional spacing is tested in a subset of the text only to get as close as possible to the correct measurement. There's a good set of code here I adapted to separate and alter the text for us.

Once the text is all calculated and updated, the text is fed into a TextBox/TextRun in the SSRS report. 

Setup Report Custom Code

To add the code needed to accomplish the task at hand, you will need to open the desired report, and go into the Report Properties and the References tab (note: screen shots are taken using Report Builder 2016). Add references to System.Drawing.dll and System.Windows.Forms.dll using the local GAC folder and finding the subfolders for each dll (default: C:\Windows\Microsoft.NET\assembly\GAC_MSIL):

reporting services justificar texto

Setup SSRS Report with TextBox

Now that we have the code in place and ready to go, we just need to create TextBox or TextRun on the SSRS report, and set it up to use the main method to create its content.

Right-click the area in the report and select Insert -> TextBox. Right-click the text box and select Expression... and enter a reference to the custom code (filling in desired values in place of the italics labels below):Variables!GiantText.Value + vbcrlf+"Blah de blah de blahblahblah! I hope this formats well here!", new System.Drawing.Font("Calibri",10.5), false, 300)

For best results, resize the textbox width to at least the expected width. Since carriage returns are inserted during formatting the text with spaces, resizing beyond the expected should not affect the line formats.

Resulting Report

Now, for the part you waded the whole way through this blog for! The results! 

reporting services justificar texto

Keep in mind that every font and text may result in a bit different appearance because the justification depends on the hair space character. This one here looks decent (The lines are really close to actual justification. This uses Calibri 10.5pt), but it just as easy to provide an example of one that looks awful using this method due to font sizing and characteristics.

Hopefully this (or this ) will help those out there in a jam on how to justify text within an SSRS report without having to yank out your hair or fork out beaucoup bucks on custom components.

Related posts

  • SQL Server Reporting Services (SSRS): How to Justify Text (Part 1) How to fully justify text in SQL Server Reporting Services (SSRS).
  • SQL Server Reporting Services (SSRS): How to Justify Text (Part 2) How to fully justify text in SQL Server Reporting Services (SSRS).
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Comments (9) -

Deevaker goel.

Hi, I am looking for justify option in SSRS, I tried the steps above. However when i write code in text box expression, it say unable to find function "TextOnlyJustify". Can you please suggest if I am missing something

Hi Deevaker, The only thing I can think would cause that error would be that the above three functions haven't first been pasted into the Report properties Code section. I am testing this in Report Builder 2016 and it successfully works for me when the functions are pasted in the Report Code section first. Thanks, Dean

Ohhhh it's amaizing!!! I've been looking for something similar for a long time. The justification is not perfect but at least something similar is achieved. Thanks for sharing your work!!

Edison Ramirez

It works perfectly .... It is a brilliant solution, it will save me several hours of work. Thank you so much for sharing it, Dean

Thank you very much for the help. Works very well. I have a question... Doing tests on a server 2008 I have an error in the line: "Dim words As String () = paragraph.Split (" "C)" But in a server 2016 it works perfect. Is there another compatible alternative?

While I don't have a 2008 server spun up to test with right now, another option for the syntax of splitting strings in VB would be: Strings.Split(paragraph, " ") Not sure if the error is caused by a difference in code options (i.e. Option Strict which enforces typing instead of trying to "fix things") set by SSRS for the custom VB code or something else here without seeing the error message you are getting.

arrangemonk

you have to reference the .net 2 linraries in reportserver 2008

Thank you so much... this is amazing!

It saved me days of work, I was really struggling on it.. This solution definitely deserves a 5 stars! Thank you very much!

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How to Justify Text in SSRS

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Justify FullJustify Text Alignment

Custom Property Name : TextAlignment Custom Property Type : String Custom Property Values : Justify, FullJustify

In report the code should be like the following:

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Aplicación de formato al texto y los marcadores de posición en informes paginados (Generador de informes)

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Un cuadro de texto puede ser un elemento de informe paginado. También puede ser una celda individual de una región de datos que contiene texto, un campo calculado, un puntero a un campo de una base de datos o una combinación de los tres elementos. Puede mezclar fuentes y colores, agregar los estilos negrita y cursiva, y usar estilos de párrafo como la alineación y las sangrías francesas. Puede dar formato a un cuadro de texto completo o a determinados números, expresiones, campos o cadenas de texto del cuadro de texto.

La fuente, el tamaño, el color y los efectos contribuyen a la legibilidad de un informe. Al texto de un cuadro de texto o de una región de datos se puede aplicar una fuente, un estilo de fuente, un tamaño de fuente y efectos de subrayado. De forma predeterminada, la fuente que se usa para los informes es Arial, 10 puntos, color negro. En los cuadros de diálogo Cuadro de texto y Propiedades de texto , puede especificar cómo deberá aparecer el texto cuando se represente el informe.

En esta ilustración, el propio cuadro de texto tiene un borde y todo el texto se encuentra en el mismo cuadro de texto, pero el texto tiene diferentes formatos.

Para más información, vea Tutorial: Dar formato a texto (Generador de informes) .

Puede crear y modificar los archivos de definición de informes paginados (.rdl) en el Generador de informes de Microsoft, en Power BI Report Builder y en el Diseñador de informes de SQL Server Data Tools.

Crear texto de marcador de posición en un cuadro de texto

Cuando se define una expresión simple o compleja dentro de un cuadro de texto, la representación resultante de esta expresión en la interfaz de usuario se conoce como marcador de posición . En un cuadro de texto, puede definir colores, fuentes, acciones y otros comportamientos de cualquier número de marcadores de posición o de secciones de texto.

El valor de un marcador de posición siempre es una expresión simple o compleja. Para agregar un marcador de posición a un cuadro de texto, puede crear una expresión mediante uno de los métodos siguientes:

Arrastre un campo desde el panel Datos de informe y colóquelo en el cuadro de texto. Si arrastra la expresión hasta cualquier otro lugar del cuerpo del informe, se creará un nuevo cuadro de texto con el marcador de posición dentro de él. El valor de este marcador de posición será la expresión de campo correspondiente al campo que se quitó.

Haga clic con el botón derecho en cualquier lugar del cuadro de texto y seleccione Insertar marcador de posición . En el cuadro de diálogo Propiedades del marcador de posición , puede especificar una expresión como el valor del marcador de posición. Para más información, vea Cuadro de diálogo Propiedades del marcador de posición, General (Generador de informes y SSRS) .

Escriba cualquier expresión simple o compleja en el cuadro de texto. Por ejemplo, si escribe Name: [Name] en el cuadro de texto, el texto [Name] se mostrará como un marcador de posición que representa la expresión =Fields!Name.Value .

En un cuadro de texto vacío, escriba una expresión que comience por un signo igual (=). Si saca el foco del cuadro de texto, la expresión resultante se convertirá en un marcador de posición que podrá editar. Si el cuadro de texto no está vacío, o si el signo igual se ha insertado en cualquier lugar que no sea el primer carácter del cuadro de texto, el signo igual se considerará un literal de cadena y no se creará ningún marcador de posición. Para más información sobre cómo definir expresiones simples y complejas, vea Usar expresiones en informes (Generador de informes y SSRS) .

Dar formato a los marcadores de posición y al texto estático de un cuadro de texto

Puede dar formato a los marcadores de posición con el cuadro de diálogo Propiedades del marcador de posición . Solo puede dar formato al marcador de posición completo, no a sus secciones. Si desea ver la expresión subyacente, puede pausar el puntero en el marcador de posición. Para cambiar la expresión subyacente, puede hacer doble clic en el marcador de posición o puede hacer clic con el botón derecho en el marcador de posición y seleccionar Propiedades del marcador de posición . También puede especificar una etiqueta de interfaz de usuario con la propiedad Label de General en el cuadro de diálogo Propiedades del marcador de posición . Este será el texto que se mostrará para el marcador de posición en tiempo de diseño.

En esta ilustración, un cuadro de texto de una lista contiene una etiqueta con formato de negrita y un marcador de posición sin formato.

A diferencia del texto de un marcador de posición, puede alinear por separado cadenas de texto individuales de un cuadro de texto, usar varios párrafos dentro de un cuadro de texto y definir otros comportamientos de cualquier subconjunto de texto.

Puede definir colores, fuentes, acciones y otros comportamientos de cualquier subconjunto de texto de un cuadro de texto y crear así una combinación de correspondencia o una plantilla para el texto del informe. También puede usar varios párrafos dentro de un mismo cuadro de texto. Por ejemplo, si tiene dos párrafos de texto independientes, puede separarlos presionando ENTRAR en el cuadro de texto. También puede establecer un valor de alineación para cualquier cadena de texto individual. Además, puede definir una acción para las distintas cadenas de texto de un cuadro de texto. Esto puede resultar útil si desea agregar un hipervínculo para una cadena de texto de un cuadro de texto.

Las acciones definidas en el cuadro de texto tienen una prioridad más alta que las acciones definidas para una cadena de texto individual de un cuadro de texto.

Para más información sobre el formato mixto, vea Dar formato al texto en un cuadro de texto (Generador de informes y SSRS) .

Alinear texto horizontal con General

En Alineación , en el cuadro de diálogo Propiedades de cuadro de texto , puede especificar cómo se debe alinear el texto horizontalmente. Si no especifica un valor para la alineación, el valor predeterminado será Predeterminado . Esto significa que el texto se alinea en función del tipo de campo del valor del marcador de posición. Si especifica una expresión que se evalúa como un valor que no es de cadena, es decir, no es un número, el texto se alinea a la derecha. Si la expresión se evalúa como un valor de cadena, como por ejemplo un número, el texto se alinea a la izquierda.

Consulte también

Expresiones (Generador de informes y SSRS) Aplicar formato a las etiquetas de los ejes de un gráfico (Generador de informes y SSRS) Aplicar formato a las escalas de un medidor (Generador de informes y SSRS) Tablas, matrices y listas (Generador de informes y SSRS) Cuadro de diálogo Propiedades del marcador de posición, General (Generador de informes y SSRS) Exportar a Microsoft Excel (Generador de informes y SSRS) Cuadros de texto (Generador de informes y SSRS)

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SQL Reporting Services Justify Text In A Textbox

I need to justify the text of my textboxes (justify both left and right). SRS only has an option for left, center, and right. Does anyone have a custom control that can do this or some tips, tricks, or ideas on how I can make the text justified? Align the text in justified format.

reporting services justificar texto

How To Align The Text In Justify Format With SQL Server Reporting Services?

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How to align the text in justify format In SQL server Reporting Services? Is there any code to do so?

How to Apply justify to textbox text in ssrs?

I'm developing an SSRS report using VS2013 Premium with SSDT - BI v12.0.2430.0. SSRS is hosted on a SQL 2014 instance.The underlying database table has a varchar(max) field which stores text and embedded image data from a third-party application.  I can extract this text, save it as an html file and open that in a browser.  It renders complete with any embedded image.Meanwhile, the report textbox has its Placeholder Properties, Markup type set to HTML.  Yet when I run the report, the text is displayed but any embedded image is not.Is there any approach I can take, perhaps transforming the varchar(max) data to another format in the query for my dataset, that can show the text and any embedded image in my report?  Or is it that the TextBox control is limited, not unreasonably, to text only?  If so, is there another control I could use, perhaps custom or third-party?

Hi, Is it possible to insert html into a text control? I have some records containing html that are saved using a website based on a richText html editor... How can i send the html to the textbox so that it would render like it is desired? If by any reason i cannot use html how can i at least specify line breaks and feeds? Best Regards, LS

We want to rotate the textbox 45 degrees. When I use properties/writing mode, change it to "Rotate270", the normal textbox "This is not" becomes the following But we want to rotate it like below, is there a way to do this in BIDS? I found this thread but not working [URL] ...

I have an Expression with two different Texts. I would life for the Left part to be Left Aligned and the Right Part be Right Aligned. Region 5 Region 2 7 However I can only use spaces and it shows up like this Region         5 Region2         7 It counts the number of spaces between the first text and second. I want it to be normalized so I figured left and right align. I have tried placeholders but the placeholders only accept 1 align. When i change the second placeholder alignment it also changes the first alignment.

We run 2014 enterprise. Can parts of the phrase that goes into a text box be forced to go to designated lines in that box?  For instance if I have the phrase aaaaa bbbbb ccccc ddddd going into my text box , can I force a carriage return after each word (eg aaaaa)  within the textbox? 

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Some textbox are great moving, and need to when the box above gets extra data.. but how do a stop one from moving? make it stay right where I put it. A stays where it is... for some reason. but B doesnt? it moves down according the textboxes to the left (where is says phone) ...

Do we have any option to increase/decrease textbox width dynamically? I know that we have option to increase or decrease height.

How do I achieve double spacing of lines in a large text box in SSRS?

I have two charts which are based on their own separate datasets.  One chart shows data aggregated by MONTH, the other chart shows data aggregated by WEEK.  I have put both of these charts inside a rectangle and set their visibility based on whether or not there is data returned by their respective datasets.  This part is working just fine. However, I have added a tablix to the report, deleted all columns and rows leaving only one remaining row/column so it looks like a textbox.  This tablix is sitting on top of the two charts.  The problem i'm having is that when both charts return no data and they do not show up in the report, the tablix still remains visible. I need to set the visibility but based on a condition between the two different datasets behind each chart. Here's what I need:  If ONE of the charts returns data, then I need the tablix to be visible.  If neither chart returns data, then I need the tablix to be invisible.  I'm trying to write an IIF statement comparing the two datasets but I get inscope errors.  Isn't it possible to compare values which are contained in two separate datasets in SSRS? Seems like something like the following logic should work: IIF(CountRows("Monthly_DataSet") > 0 OR CountRows("Weekly_DataSet") > 0 , FALSE, TRUE) Obviously the above expression will return syntax errors, but you'll get the point as to how i'm thinking. How can I set the visibility of the tablix based on these two charts?

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I have designed a form and created two parameter fields to accept username and password from the user. Based on the values entered above, I am validating inside a stored procedure. I am unable to mask the text the user enters in the password field. I could not locate any mask property. Anybody can help me?

I was trying to write a custom legend text for a chart that I have in SSRS. In the chart I have a Bar chart and a Line chart. I have two values coming from a dataset. One is a running value. All the series values are from year dataset. I need to get a custom legend text for the three data series looking like this. "2013- Mth", "2014-Mth". Year should be dynamic and coming from the dataset. I tried writing an expression in the series legend option as shown below. But I don't get the required text for the chart. I only get the default series text for the legend. If I only write a text without the dynamic year taken from the dataset columns I get the custom text. But not when I concatenate the dynamic year series with the static text. Any property to enable/disable?

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I tried creating Toggle Option over a Text box to Show the Image on Click but Since the Toggle refreshes the entire report user faces performance issue. Is there any other option to avoid the Toggle Refreshing the report or to show an image on Click of an Text Box?

When I install SQL Server 2005 Express Edition with Advanced Services SP2 on Windows Vista, Reporting Services and Full-Text Search are not being installed. My user account is configured as a Standard User. When I initiate the installation, I'm prompted for the password for the administrator user account. During the System Configuration Check, I get a warning for the IIS Feature Requirement action. The associated message says: "Microsoft Internet Information Services (IIS) is either not installed or is disabled. IIS is required by some SQL Server features. Without IIS, some SQL Server features will not be available for installation. To install all SQL Server features, install IIS from Add or Remove Programs in Control Panel or enable the IIS service through the Control Panel if it is already installed, and then run SQL Server Setup again. For a list of features that depend on IIS, see Features Supported by Editions of SQL Server in Books Online." KB Article 920201 ("You receive a warning message on the System Configuration Check page of the SQL Server 2005 Setup program on a computer that is running Windows Vista or a Server Core installation of Windows Server "Longhorn"") seems to address this issue. I used the Windows Features applet and selected all of the Internet Information Services items that were listed in the KB article; however, the "Windows Authentication" item was not in my list. ("IIS Metabase" and "IIS 6 WMI" were in my list but were worded differently--"IIS Metabase and IIS 6 configuration compatibility" and "IIS 6 WMI Compatibility", respectively--but I selected them both.) When I re-ran the SQLEXPR_ADV installer, I got the same warning...and Reporting Services and Full-Text Search were still not installed. I went back into the Windows Features applet and selected all of the remaining unselected "Internet Information Services" items, and then re-ran the SQLEXPR_ADV installer. I got the same warning...and Reporting Services and Full-Text Search were still not installed. It's frustrating that there is no obvious reason or error message as to why Reporting Services and Full-Text Search are not being installed. Are these features compatible with Windows Vista? Does anyone have an idea as to what the problem might be?

I have the following text field in SSRS report: Version 2.2.32.7 1.0.0.0 2.0.0.0 1.2.0.0 2.1.8.8 1.4.11.0 I want to sort this field interactively.I have already sorted other fields, but as this field is text but has decimal data, its not sorting properly. How do I do this correctly? Once sorted ascending, report should show Version    1.0.0.0    1.2.0.0    1.4.11.0    2.0.0.0    2.1.8.8    2.2.32.7

I am using SSRS 2008 R2 Report Builder 3.0 (10.50.4276.0) . I have simple set of data which has a persons Title and Name e.g. Mr Smith, Miss Jones, Doctor Foster The report has a parameter where the user can select which records to show based on the matching titles (Mr, Miss, Doctor) The Query for the report uses Title in (@Title) where @Title is the only parameter which can take multiple values. The report works correctly for any 1 value selected, but as soon as 2 or more values are ticked in the drop down, it fails. I believe the parameter value is being passed into the query with a comma separating the values e.g. Mr,Miss which causes the IN statement to give an error, as the statement would be where Title IN ('Mr,Miss') which does not match any of the data values. The parameter value passed needs to be 'Mr','Miss' for the IN statement to work. What statement do I have to put in the report query to get it to select any of the data rows where the title matches any 1 of the selected values?

I need to set a field value based on two date time parameter's.What is the correct syntax to allow me to pass the value into the field in my SSRS expression ? =IIf(Parameters!EndDate > Parameters!StartDate.Value, "Overdue")

I was trying to export a report which contains a number format. When I do that, all the numbers in excel will have a green small tag beside it saying "Convert from Number to Text". Is there anyway that I can change the format to a number when I export it to excel?

on this report, am having ids separated by '^'.when I export to excel, I wrote the expression as =Replace(Fields!Id.Value,"^",Environment.NewLine) It is working fine, but the problem is if I have only one id in some scenario, then this case that cell is showing an error "The Number in this cell formatted as text or precedence by apostrophe" .But in other scenario,If the ids are separated by "^", then this case that cell wont show any error. So I need to display the cell wont have any error symbol  if I have only one id .How can I achieve this?.

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social influence essay

Social Influence Revision Notes

Saul Mcleod, PhD

Educator, Researcher

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Social influence is the process by which an individual’s attitudes, beliefs or behavior are modified by the presence or action of others. Four areas of social influence are conformity, compliance and obedience, and minority influence.

Conformity (Majority Influence)

Conformity is a type of social influence defined as a change in belief or behavior in response to real or imagined social pressure. It is also known as majority influence.

Types of Conformity

Compliance ao1.

This refers to instances where a person may agree in public with a group of people, but the person privately disagrees with the group’s viewpoint or behavior. The individual changes their views, but it is a temporary change.

For example, a person may laugh at a joke because their group of friends find it funny but deep down the person does not find the joke funny.

For a study on compliance refer to Asch’s Line Study .

Internalisation AO1

Publicly changing behavior to fit in with the group while also agreeing with them privately. An internal (private) and external (public) change of behavior. This is the deepest level of conformity were the beliefs of the group become part of the individual’s own belief system.

An example of internalisation is if someone lived with a vegetarian at university and then decides to also become one too because they agree with their friend’s viewpoint / someone converting religions would also be a good example.

For a study on internalisation refer to Jenness (see below).

Identification AO1

Identification occurs when someone conforms to the demands of a given social role in society. For example, a policeman, teacher or politician. This type of conformity extends over several aspects of external behavior. However, there still be no changed to internal personal opinion.

A good example is Zimbardo’s prison study .

AO2 Scenario Question

Jan and Norah have just finished their first year at university where they lived in a house with six other students. All the other students were very health conscious and ate only organic food. Jan had listened to their point of view and now she also eats only organic food.

Norah was happy to eat organic food while in the house, but when she went home for the holidays she ate whatever her mother cooked. Both girls conformed, but for different reasons.

Explain which type of conformity each girl was showing.

“Jan shows internalisation. She has publicly and privately changed her attitudes and now permanently only eats organic food. Norah is showing compliance. She only conformed publicly to her friends’ behavior but had obviously not privately undergone attitude change to eating organic as she reverted to eating non-organic in the holidays. Norah probably conformed to gain group approval and membership whereas Jan believed the other students to be ‘right’ in their belief that organic food was ‘good’.”

Explanations for Conformity

Normative influence (ao1/ao3).

cartoon girl smoking

Normative social influence is where a person conforms to fit in with the group because they don’t want to appear foolish or be left out. Normative social influence is usually associated with compliance,

where a person changes their public behavior but not their private beliefs.

For example, a person may feel pressurised to smoke because the rest of their friends are. Normative Social influence tends to lead to compliance because the person smokes just for show but deep down they wish not to smoke. This means any change of behavior is temporary .

For a study on normative influence refer to Asch .

Informational Influence (AO1/AO3)

Informational social influence is where a person conforms because they have a desire to be right , and look to others who they believe may have more information.

This type of conformity occurs when a person is unsure of a situation or lacks knowledge and is associated with internalisation .

An example of this is if someone was to go to a posh restaurant for the first time, they may be confronted with several forks and not know which one to use, so they might look to a near by person to see what fork to use first.

For a study on informational influence refer to Jenness (see below).

Jenness’ Bean Jar Experiment AO1

Jenness carried out a study into conformity – in his experiment participants were asked to estimate how many beans they thought were in a jar. Each participant had to make an individual estimate, and then do the same as a group.

He found that when the task was carried out in a social group, the participants would report estimates of roughly the same value (even though they had previously reported quite different estimates as individuals).

The study was successful in showing majority influence, thus proving that individuals” behavior and beliefs can be influenced by a group. Additionally, this is likely to be an example of informational social influence as participants would be uncertain about the actual number of beans in the jar.

Variables Affecting Conformity

Asch’s line study ao1.

asch line study

Asch wanted to investigate whether people would conform to the majority in situations where an answer was obvious.

Procedure : In Asch’s study there were 5-7 participants per group. Each group was presented with a standard line and three comparison lines. Participants had to say aloud which comparison line matched the standard line in length. In each group there was only one real participant the remaining 6 were confederates. The confederates were told to give the incorrect answer on 12 out of 18 trails.

Results : Real participants conformed on 32% of the critical trials where confederates gave the wrong answers. Additionally, 75% of the sample conformed to the majority on at least one trial.

Evaluation of Asch’s Study AO3

  • This study lacks ecological validity as it was based on peoples’ perception of lines, this does not reflect the complexity of real life conformity.
  • There are also sampling issues regarding this study as the study was only carried out on men thus the sample was gender bias and therefore the results cannot be applied to females. The sample therefore lacks population validity.
  • Moreover, there are ethical issues regarding Asch’s study – Mention deception as participants were told the study was about perception of lines. As a result, they could not give informed consent. Furthermore, it is possible that the participants may have felt embarrassed when the true nature of the study was revealed. Thus could potentially put them through some form of psychological harm. However, Asch did debrief at the end.
  • For extra AO3 points link Asch’s results to theories/reasons why people may conform to the majority. For instance, some participants said they conformed to fit in with the group, this claim coincides (supports) ‘Normative influence’ which states that people conform to fit in when privately disagreeing with the majority.

Factors Affecting Conformity AO3

In further trials, Asch (1952, 1956) changed the procedure (i.e., independent variables) to investigate which situational factors influenced the level of conformity (dependent variable).  His results and conclusions are given below:

Asch altered the number of confederates in his study to see how this effected conformity. The bigger the majority group (number of confederates), the more people conformed, but only up to a certain point.

With one other person (i.e., confederate) in the group conformity was 3%, with two others it increased to 13%, and with three or more it was 32% (or 1/3). However, conformity did not increase much after the group size was about 4/5.

Because conformity does not seem to increase in groups larger than four, this is considered the optimal group size.

group size

Brown and Byrne (1997) suggest that people might suspect collusion if the majority rises beyond three or four.

According to Hogg & Vaughan (1995), the most robust finding is that conformity reaches its full extent with 3-5 person majority, with additional members having little effect.

Group Unanimity

A person is more likely to conform when all members of the group agree and give the same answer.

When one other person in the group gave a different answer from the others, and the group answer was not unanimous, conformity dropped. Asch (1951) found that even the presence of just one confederate that goes against the majority choice can reduce conformity as much as 80%.

Difficulty of Task

When the (comparison) lines (e.g., A, B, C) were made more similar in length it was harder to judge the correct answer and conformity increased.

When we are uncertain, it seems we look to others for confirmation. The more difficult the task, the greater the conformity.

Answer in Private

When participants were allowed to answer in private (so the rest of the group does not know their response) conformity decreases. This is because there are fewer group pressures and normative influence is not as powerful, as there is no fear of rejection from the group.

Conformity to Social Roles

Social roles are the part people play as members of a social group (e.g. student, teacher, policeman etc). There is considerable pressure to conform to the expectations of a social role. Conforming to a social role is called identification.

Stanford Prison Experiment AO1

Zimbardo wanted to investigate how readily people would conform to the social roles of guard and prisoner in a role-playing exercise that simulated prison life.

Procedure : To study the roles people play in prison situations, Zimbardo converted a basement of the Stanford University psychology building into a mock prison.

He advertised for students to play the roles of prisoners and guards for a fortnight. Participants were randomly assigned to either the role of prisoner or guard in a simulated prison environment.

stanford prison experiment picture of a prisoner being arrested

Prisoners were issued a uniform, and referred to by their number only. Guards were issued a khaki uniform, together with whistles, handcuffs and dark glasses, to make eye contact with prisoners impossible. The guards worked shifts of eight hours each (the other guards remained on call). No physical violence was permitted.

Zimbardo observed the behavior of the prisoners and guards (as a researcher), and also acted as prison warden.

Findings : Within a very short time both guards and prisoners were settling into their new roles, with the guards adopting theirs quickly and easily. Within hours of beginning the experiment some guards began to harass prisoners. T

hey behaved in a brutal and sadistic manner, apparently enjoying it. Other guards joined in, and other prisoners were also tormented.

The prisoners soon adopted prisoner-like behavior too. They talked about prison issues a great deal of the time. They ‘told tales’ on each other to the guards. They started taking the prison rules very seriously, and some even began siding with the guards against prisoners who did not obey the rules.

As the prisoners became more submissive, the guards became more aggressive and assertive. They demanded ever greater obedience from the prisoners.

The prisoners were dependent on the guards for everything so tried to find ways to please the guards, such as telling tales on fellow prisoners.

Evaluation of Zimbardo’s Study AO3

  • Demand characteristics could explain the findings of the study. Most of the guards later claimed they were simply acting. Because the guards and prisoners were playing a role their behavior may not be influenced by the same factors which affect behavior in real life. This means the study’s findings cannot be reasonably generalized to real life, such as prison settings. I.e the study has low ecological validity.
  • The study may also lack population validity as the sample comprised US male students. The study’s findings cannot be applied to female prisons or those from other countries. For example, America is an individualist culture (were people are generally less conforming) and the results maybe different in collectivist cultures (such as Asian countries) .
  • A strength of the study is that it has altered the way US prisons are run. For example, juveniles accused of federal crimes are no longer housed before trial with adult prisoners (due to the risk of violence against them).
  • The study has received many ethical criticisms, including lack of fully informed consent by participants as Zimbardo himself did not know what would happen in the experiment (it was unpredictable). Also, the prisoners did not consent to being “arrested” at home.
  • Also, participants playing the role of prisoners were not protected from psychological harm, experiencing incidents of humiliation and distress. For example, one prisoner had to be released after 36 hours because of uncontrollable bursts of screaming, crying and anger. However, in Zimbardo’s defence the emotional distress experienced by the prisoners could not have been predicted from the outset. In addition Zimbardo did conduct debriefing sessions for several years afterwards and concluded they were no lasting negative effects.
  • Another strength of the study is that the harmful treatment of participant led to the formal recognition of ethical guidelines . Studies must now gain ethical approval before they are conducted. An ethics committee review whether the potential benefits of the research are justifiable in the light of possible risk of physical or psychological harm. They may request researchers make changes to the studies design or procedure, or in extreme cases deny approval of the study altogether.
Obedience is a type of social influence where a person follows an order from another person who is usually an authority figure.

Explanations for Obedience

Milgram’s shock study ao1.

Milgram wanted to know why Germans were willing to kill Jews during the Holocaust. He thought that it might have been because German’s were just evil.

He thought that Americans were different and would not have followed such orders. To test this ‘German’s are different’ hypothesis he carried out this study (outlined below).

milgram obedience

Procedure : Milgram wanted to see whether people would obey a legitimate authority figure when given instructions to harm another human being.

He conducted a lab experiment in which two participants were assigned either the role of a teacher (this was always given to the true participant) or learner (a confederate called Mr. Wallace).

The teacher and learner were put into separate rooms. The teacher was then asked by the experimenter (who wore a lab coat) to administer electric shocks (which were actually harmless) to the learner each time he gave the wrong answer. These shocks increased every time the learner gave a wrong answer, from 15 – 450 volts.

milgram scale

The experimenter (Mr Williams) wore a grey lab coat and his role was to give a series of orders / prods when the participant refused to administer a shock. There were 4 prods and if one was not obeyed then the experimenter read out the next prod, and so on.

  • Prod 1: please continue.
  • Prod 2: the experiment requires you to continue.
  • Prod 3: It is absolutely essential that you continue.
  • Prod 4: you have no other choice but to continue.

Results : The results were that all participants went to 300 volts and 65% were willing to go all the way to 450 volts. Milgram did more than one experiment – he carried out 18 variations of his study.

All he did was alter the situation (IV) to see how this affected obedience (DV). For example, when the experimenter instructed and prompted the teacher by telephone from another room, obedience fell to 20.5%.

Evaluation of Milgram’s Study AO3

  • A limitation is that this study lacked ecological validity as it was carried out in a lab under artificial conditions. This means that it might not be possible to generalise the finding to a real life setting, as people do not usually receive orders to hurt another person in real life.
  • Another problem is that the sample was biased. Milgram only used males in his study and this means we cannot generalise the results to females.
  • Highlight the value that Milgram’s work has provided to social Psychology. For instance Milgram’s work gives an insight into why people under the Nazi reign were willing to kill Jews when given orders to do so. It also highlights how we can all be blind to obedience often doing things without question.
  • A strength of the study is that it used a standardised procedure because it was a lab experiment. This is good because it improves the reliability of the study and also helps establish a causal relationship.

Ethical Issues AO3

  • Deception – the participants actually believed they were shocking a real person, and were unaware the learner was a confederate of Milgram’s.

However, Milgram argued that “illusion is used when necessary in order to set the stage for the revelation of certain difficult-to-get-at-truths”.

Milgram also interviewed participants afterwards to find out the effect of the deception. Apparently 83.7% said that they were “glad to be in the experiment”, and 1.3% said that they wished they had not been involved.

  • Protection of participants – Participants were exposed to extremely stressful situations that may have the potential to cause psychological harm. Many of the participants were visibly distressed.

Signs of tension included trembling, sweating, stuttering, laughing nervously, biting lips and digging fingernails into palms of hands. Three participants had uncontrollable seizures, and many pleaded to be allowed to stop the experiment.

Full blown seizures were observed for 3 participants; one so violent that the experiment was stopped.

In his defence, Milgram argued that these effects were only short term. Once the participants were debriefed (and could see the confederate was OK) their stress levels decreased. Milgram also interviewed the participants one year after the event and concluded that most were happy that they had taken part.

  • However, Milgram did debrief the participants fully after the experiment and also followed up after a period of time to ensure that they came to no harm.

The Agentic State

Agency theory says that people will obey an authority when they believe that the authority will take responsibility for the consequences of their actions. This is supported by some aspects of Milgram’s evidence.

For example, when participants were reminded that they had responsibility for their own actions, almost none of them were prepared to obey. In contrast, many participants who were refusing to go on did so if the experimenter said that he would take responsibility’.

Another example of the agenetic state involved a variation of Milgram’s study whereby participants could instruct an assistant (confederate) to press the switches. In this condition 92.5% shocked to the maximum 450 volts. This shows when there is less personal responsibility obedience increases.

Limitations AO3

  • Cannot explain Nazi behavior – Mandel described how the German Police Reserve shot civilians in a small Polish town even though they were not directly ordered to and were told they could be assigned to other duties – Challenges agentic state as they were not powerless to obey.
  • May be better explained by ‘plain cruelty’ – Zimbardo’s participants may have used the situation to express their sadistic tendencies, guards inflicted rapidly escalating cruelty to prisoners even though there was no authority figure telling them to – Obedience may be caused by certain aspects of human nature.

Legitimacy of Authority Figure

Most societies are hierarchal (parents, teachers and police officers hold authority over us). The authority they use is legitimate as it is argued by society, helping it to run smoothly. One of the consequences is that some people are granted the power to punish others.

People tend to obey others if they recognise their authority as morally right and / or legally based (i.e. legitimate). This response to legitimate authority is learned in a variety of situations, for example in the family, school and workplace.

With regard to Milgram” study the experimenter is seen as having legitimate authority as he has scientific status.

If an authority figure’s commands are potentially harmful, for it to be perceived as legitimate they must occur within some type of institutional structure (e.g. a university or the military).

Situational Factors

The Milgram experiment was carried out many times whereby Milgram varied the basic procedure (changed the IV). By doing this Milgram could identify which situational factors affected obedience (the DV).

Obedience was measured by how many participants shocked to the maximum 450 volts (65% in the original study).

Authority Figure Wearing a Uniform

Milgram’s experimenter (Mr. Williams) wore a laboratory coat (a symbol of scientific expertise) which gave him a high status. But when the experimenter dressed in everyday clothes obedience was very low. The uniform of the authority figure can give them status.

Status of Location

Milgram’s obedience experiment was conducted at Yale, a prestigious university in America. The high status of the university gave the study credibility and respect in the eyes of the participants, thus making them more likely to obey.

When Milgram moved his experiment to a set of run down offices rather than the impressive Yale University obedience dropped to 47.5%. This suggests that status of location effects obedience.

Proximity of Authority Figure

People are more likely be obey an authority figure who is in close proximity (i.e. nearby). In Milgram’s study the experimenter was in the same room as the participant (i.e. teacher).

If the authority figure is distant it is easier to resistant their orders. When the experimenter instructed and prompted the teacher by telephone from another room, obedience fell to 20.5%. Many participants cheated and missed out shocks or gave less voltage than ordered to by the experimenter.

Dispositional Explanation: Authoritarian Personality

Adorno felt that personality (i.e. dispositional) factors rather than situational (i.e. environmental) factors could explain obedience. He proposed that there was such a thing as an authoritarian personality, i.e. a person who favours an authoritarian social system and, admires obedience to authority figures.

One of the various characteristics of the authoritarian personality is that the individual is hostile to those who are of inferior status, but obedient of people with high status.

He investigated 2000 middle class, white Americans and their unconscious attitudes towards other racial groups using the F-scale to measure authoritarian personality

  • Adorno found many significant correlations (e.g. Authoritarianism correlated with prejudice against minority groups) but we cannot say that one variable causes another – Adorno cannot claim that a harsh parenting style caused a development of an Authoritarian personality, we must consider other explanations like legitimacy of authority.
  • Millions of individuals in Germany displayed obedient behavior but didn’t have the same personality, it is unlikely that the majority of Germany’s population possessed an authoritarian personality – An alternative explanation like social identity theory (people identify with groups they are apart with and discriminate against ones they are not) may be more realistic.
  • May be better explanations – Prejudice and submissiveness could just as easily be caused by a poor standard of education as a child – Theory lacks internal validity as it assumes obedience is caused by dispositional explanations when it may be situational variables.
  • Adorno used a biased sample – Only used 2000 middle class white Americans who are more likely to have an Authoritarian personality due to demographics and the time of the study – Research lacks population validity and historical validity, so conclusions cannot be generalised to people outside the sample.

Resistance to Social Influence

Independent behavior is a term that psychologists use to describe behavior that seems not be influenced by other people. This happens when a person resists the pressures to conform or obey.

Social Support

In one of Asch’s experimental variations he showed that the presence of a dissident (a confederate who did not conform) led to a decrease in the conformity levels in true participants.

This is thought to be because the presence of a dissident gave the true participant social support and made them feel more confident in their own decision and more confident in rejecting the majority position.

Social support also decreases obedience to authority. In a variation of Milgram” study two other participants (confederates) were also teachers but refused to obey. Confederate 1 stopped at 150 volts and confederate 2 stopped at 210 volts. The presence of others who are seen to disobey the authority figure reduced the level of obedience to 10%.

Locus of Control

The term ‘ Locus of control ’ refers to how much control a person feels they have in their own behavior. A person can either have an internal locus of control or an external locus of control.

There is a continuum, with most people lying in between.

People with a high internal locus of control perceive (see) themselves as having a great deal of personal control over their behavior and are therefore more likely to take responsibility for the way they behave. For example, I did well on the exams because I revised extremely hard.

In contrast a person with a high external locus of control perceive their behaviors as being a result of external influences or luck – e.g. I did well on the test because it was easy.

Research has shown that people with an internal locus of control tend to be less conforming and less obedient (i.e. more independent). Rotter proposes that people with internal locus of control are better at resisting social pressure to conform or obey, perhaps because they feel responsible for their actions.

Minority Influence

Minority influence occurs when a small group (minority) influences the opinion of a much larger group (majority). This can happen when the minority behaves in the following ways.

Consistency

Moscovici stated that being consistent and unchanging in a view is more likely to influence the majority than if a minority is inconsistent and chops and changes their mind.

Procedure : Moscovici conducted an experiment in which female participants were shown 36 blue slides of different intensity and asked to report the colours. There were two confederates (the minority) and four participants (the majority).

In the first part of the experiment the two confederates answered green for each of the 36 slides. They were totally consistent in their responses. In the second part of the experiment they answered green 24 times and blue 12 times. In this case they were inconsistent in their answers. A control group was also used consisting of participants only – no confederates.

Findings : When the confederates were consistent in their answers about 8% of participants said the slides were green. When the confederates answered inconsistently about 1% of participants Said the slides were green.

A distinction can be made between two forms of consistency:

(a) Diachronic Consistency – i.e. consistency over time – the majority sticks to its guns, doesn’t modify its views. (b) Synchronic Consistency – i.e. consistency between its members – all members agree and back each other up.

Consistency may be important because:

1. Confronted with a consistent opposition, members of the majority will sit up, take notice, and rethink their position (i.e. the minority focuses attention on itself). 2. A consistent minority disrupts established norms and creates uncertainty, doubt and conflict. This can lead to the majority taking the minority view seriously. The majority will therefore be more likely to question their own views.

When the majority is confronted with someone with self-confidence and dedication to take a popular stand and refuses to back own, they may assume that he or she has a point.

Flexibility

A number of researchers have questioned whether consistency alone is sufficient for a minority to influence a majority. They argue that the key is how the majority interprets consistency. If the consistent minority are seen as inflexible, rigid, uncompromising and dogmatic, they will be unlikely to change the views of the majority.

However, if they appear flexible and compromising, they are likely to be seen as less extreme, as more moderate, cooperative and reasonable. As a result, they will have a better chance of changing majority views.

Some researchers have gone further and suggested that it is not just the appearance of flexibility and compromise which is important but actual flexibility and compromise. This possibility was investigated by Nemeth.

Their experiment was based on a mock jury in which groups of three participants and one confederate had to decide on the amount of compensation to be given to the victim of a ski-lift accident. When the consistent minority (the confederate) argued for a very low amount and refused to change his position, he had no effect on the majority.

However, when he compromised and moved some way towards the majority position, the majority also compromised and changed their view.

This experiment questions the importance of consistency. The minority position changed, it was not consistent, and it was this change that apparently resulted in minority influence.

(a) Name 3 behaviors that enable a minority to influence a majority. (3 marks)

(b) Marcus wants to persuade his group of friends to go travelling in the summer but the rest of the group would like to go on a beach holiday.

Briefly suggest how Marcus might use the 3 behaviors that you have identified in your answer to (a) to persuade his friends to go travelling. (3 marks)

(Total 6 Marks)

(a) Answer. “Consistency, Commitment, Flexibility.” (No need to explain – just name them). (b) Answer. “Marcus should consistently give the same message again and again that the group should go travelling rather than on a beach holiday. He should show commitment to his idea by, for example, investing time in planning and organising his proposed trip. Lastly, he should some flexibility: for example, he could suggest the group go travelling but they will spend quite a bit of time at the beach whilst travelling.”

Social Change

Social change occurs when a whole society adopts a new belief or behavior which then becomes widely accepted as the ‘norm’ which was not before. Social influence processes involved in social change include minority influence (consistency, commitment and flexibility), internal locus of control and disobedience to authority.

Social change is usually a result of minority influence . This is when a small group of people (the minority) manage to persuade the majority to adopt their point of view.

This also links to independent behavior, because the minority resists pressures to conform and/or obey. Usually the minority have an internal locus of control.

Committed minorities, such as those who risk themselves for their cause has an effect on the majority through an augmentation principle, this means the majority value the importance of the cause – as the minority are risking their lives for it.

Through these processes more and more of the majority will gradually change towards the cause resulting in the snowball effect which will ultimately result in societal change, once this has happened social cryptomnesia occurs which is when people can remember a change but not how it came about.

Moscovici found that consistency is the most important factor in deciding whether the minority are influential or not. This means that the minority must be clear on what they are asking for and not change their minds, or disagree amongst themselves. This creates uncertainty amongst the majority.

Moscovici investigated the importance of consistency. He had a group of 6 participants and a range of blue/ green slides varying in intensity – they all had to state the colour they saw.

The study had two conditions, confederates who consistently said green and an inconsistent group and a control group with no confederates. He found that the consistent minority group had a greater effect on the other participants than the inconsistent group. This confirms that consistency is a major factor in minority influence.

It has been found that once the minority begin to persuade people round to their way of thinking, a snowball effect begins to happen. This means that more and more people adopt the minority opinion, until gradually the minority becomes the majority.

At this point, the people who have not changed their opinion are the minority, and they will often conform to the majority view as a result of group pressures.

The majority opinion then becomes law, and people have to obey this law. Once this happens, the minority opinion has become the dominant position in society, and people do often not even remember where the opinion originated from. This is a process known as crypto amnesia .

Further social influence research from Asch and Milgram demonstrates that a minority can have an affect on the majority – both studies involved a dissenter or disobedient role model who influenced the behavior of the majority. However, there are methodological issues in these areas of research: these studies are both based on artificial tasks (judging line lengths).

The application of minority influence is further limited due to the importance of identification which is overlooked in minority influence research. Psychologists have suggested that people are less likely to behave in environmentally friendly ways due to the negative connotations associated with them (“tree huggers”).

Minorities wanting social change should avoid behaviors that reinforce social change – essentially off-putting to the majority.

This suggests that being able to identify with a minority group is just as important as agreeing with their views in order to change the behavior of the major.

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Hypothesis and theory article, social influence in adolescent decision-making: a formal framework.

social influence essay

  • 1 Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
  • 2 Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
  • 3 Department of Developmental Psychology, University of Amsterdam, Amsterdam, Netherlands

Adolescence is a period of life during which peers play a pivotal role in decision-making. The narrative of social influence during adolescence often revolves around risky and maladaptive decisions, like driving under the influence, and using illegal substances ( Steinberg, 2005 ). However, research has also shown that social influence can lead to increased prosocial behaviors ( Van Hoorn et al., 2017 ) and a reduction in risk-taking ( Braams et al., 2019 ). While many studies support the notion that adolescents are more sensitive to peer influence than children or adults, the developmental processes that underlie this sensitivity remain poorly understood. We argue that one important reason for this lack of understanding is the absence of precisely formulated models. To make a first step toward formal models of social influence during adolescence, we first identify three prominent verbal models of social influence in the literature: (1) social motivation, (2) reward sensitivity, and (3) distraction. We then illustrate how these can be translated into formal models, and how such formal models can inform experimental design and help identify developmental processes. Finally, by applying our formal models to existing datasets, we demonstrate the usefulness of formalization by synthesizing different studies with seemingly disparate results. We conclude with a discussion on how formal modeling can be utilized to better investigate the development of peer influence in adolescence.

Introduction

Peers impact almost all aspects of adolescent lives, from the more trivial, such as taste in music and clothing, to the more serious, such as the use of illicit drugs or engaging in unprotected sex ( Steinberg, 2008 ). These latter, riskier, choices may carry life-long consequences for the adolescent and bring significant cost to society. It is empirically well established that the presence of peers influences risky behavior in adolescence ( Gardner and Steinberg, 2005 ; Chein et al., 2011 ; Pfeifer et al., 2011 ; Smith et al., 2014 ), but the underlying developmental processes remain poorly understood. Understanding these processes, however, is important for at least two reasons. First, empowering adolescents to become more competent decision-makers will be more effective if we succeed at tailoring interventions to their developmental affordances. Second, we can only identify these affordances if we succeed at linking adolescent neuronal and cognitive development with adolescent behavior across different social contexts.

Here we argue that this link cannot be made without formal models of adolescent peer influence. In this article we thus aim to take the first steps toward a quantitative and testable framework of adolescent social influence. Adolescence is marked by several developmental changes which offer multiple biological explanations of social influence on adolescent decision making. We refer to the current theoretical perspectives of these changes as “verbal models.” Verbal models are distinct from formal models in that they do not make quantitative predictions. In order to establish formal models that do make quantitative predictions, we first review existing verbal models and the associated empirical findings about social influence in adolescents, focusing on risky decision-making. We identify three verbal models of social influence which can be subject to developmental change; these are then formalized by grounding them in expected utility theory. Next, we show that our formal models can reliably be recovered and therefore can be used to compare hypotheses via quantitative model comparison. Finally, we fit these models to existing data and reveal previously overlooked patterns of peer influence. We conclude with a discussion on how the specificity provided by this formal approach contributes to a deeper understanding of the developmental processes behind social influence.

Social Influence on Adolescent Decision-Making

We identify three main families of verbal models in the existing literature, hereafter named as follows: (i) social motivation model, (ii) reward sensitivity model, and (iii) distraction model. These three models focus on two distinct neurodevelopmental explanations of altered decision-making during adolescence. Social motivation verbal models stress the importance of the developing “social brain.” The other two verbal models ( reward sensitivity and distraction ) both emphasize the relatively slow maturation of cognitive control systems. Previous works that fall into the reward sensitivity family of verbal models often refer to it as “dual-systems” models, as they also stress the relatively fast maturation of reward-processing brain regions and explain adolescent behavior with the maturational imbalance between reward processing and cognitive control brain regions ( Casey et al., 2008 ; Steinberg, 2008 ; Geier et al., 2010 ; Shulman et al., 2016 ). By contrast, the distraction model has a single focus on the development of cognitive control. Our subsequent review of the existing experimental evidence shows that all three of these families of verbal models are currently equally well supported in the literature, even though each model provides a different explanation for similar observations.

Verbal Models: Social Motivation

The first verbal model we consider states that adolescents have increased social motivation. Demonstrating risky behavior, or conforming to behavior of the peer group, are considered ways to reach these social goals. In other words, social motivation models assume that during adolescence there are situations where a high social value is attributed to displaying risky behavior ( Crone and Dahl, 2012 ; Ruff and Fehr, 2014 ) which is independent from the non-social value of the outcome (e.g., money).

Verbal Models: Reward Sensitivity

The verbal reward sensitivity model is based on research which suggests that adolescence is the time where fast maturation of reward processing brain systems coincides with relatively slow maturation of cognitive control systems. According to the reward sensitivity model, the biological imbalance between these two systems gives rise to risky adolescent decision-making ( Casey et al., 2008 ; Ernst et al., 2015 ; Shulman et al., 2016 ). Here we will not address the debate concerning the validity ( Pfeifer and Allen, 2016 ) or the different variants of these models ( Casey et al., 2008 ; Steinberg, 2008 ; Larsen and Luna, 2018 ). Instead, we focus on the element that is suggested to be most relevant for understanding developmental changes in peer influence: reward sensitivity. Reward sensitivity states that social influence has such dramatic effects on adolescent risk-taking because a social context “may sensitize the incentive processing system to respond to cues signaling the potential rewards of risky behavior” ( Chein et al., 2011 , p. 2). Indeed, Chein et al. (2011) showed that while being observed during a risk-taking task, brain regions related to reward processing were more active in adolescents than in adults. This was interpreted as evidence for a reward sensitivity model as it suggests that, in adolescents, the social context itself leads to changes in the processing of rewards in general.

Verbal Models: Distraction

The relatively slow maturation of cognitive control brain regions forms the basis of a third verbal model that we call “distraction model.” Here, maturational imbalance and arousal is not only specifically associated with altered representations of reward but more generally with poor self-control and diminishing cognitive skills in emotionally salient situations ( Dumontheil, 2016 ). This lack of self-control can lead adolescents to show more erratic or distracted behaviors in a social as compared to a solitary context. The distraction model does not assume any changes in value computation, but rather suggests that behavioral changes are due to stochasticity in the decision process.

Social motivation, reward sensitivity and distraction models do not assume mutually exclusive processes. Although it is plausible that the defining processes emphasized in each of these models simultaneously impact peer influence, it is important to examine which are most relevant in a particular context.

This is essential because different models provide different footholds for interventions. For example: if adolescent risk-taking is subject to social motivation it can be fruitful to provide other, less risky, means to acquire social status for instance by using meaningful roles interventions ( Ellis et al., 2016 , see also: Yeager et al., 2018 ). Adolescent reward sensitivity suggests it is useful to prohibit teens from gathering in risky situations. For instance, many states in the United States and Canada prohibit teenage drivers from taking other teenage passengers along. Distraction suggests that training in mindfulness and meditation are a good prospect for increasing desirable behaviors in adolescence ( Kuyken et al., 2013 ). These implications for interventions underscore how crucial it is to comprehend the most relevant determinants of adolescent behavior in a given context. We therefore inspect experimental work which manipulated aspects of social contexts with respect to the three verbal models of adolescent social influence: (i) social motivation, (ii) reward sensitivity, and (iii) distraction.

Seeing and Being Seen – Empirical Studies of Social Influence

Despite the complexity of social exchange, studies investigating social influence can be roughly divided into two types of situations: those where the participant observes others and those where the participant is being observed. In the light of this distinction, we review experimental studies about peer influence in adolescent risky decision-making.

Observing Others

When uncertain of what to do, observing the behavior of others can help with making a decision. Monetary lotteries are often used as an experimental setting with uncertain prospects, wherein the effect of observing the behavior of others can be investigated. In such experiments, participants observe others’ previous decisions ( Blankenstein et al., 2016 ; Reiter et al., 2019 ) or receive explicit advice ( Haddad et al., 2014 ) while making private decisions. These studies suggest that the impact of social information is greatest in early to mid-adolescence and then declines with age. Notably, in a recent study, adolescents were influenced more by safe than by risky advice ( Braams et al., 2019 ). However, currently evidence seems most in line with models that emphasize social motivation, as an increase in safe decisions is not predicted by reward sensitivity models. A small increase of participant safe choices in studies such as Braams et al. (2019) however, could also be attributed to a greater distraction during adolescence. Notably, none of these studies provided adolescents with information about the outcomes of others’ decisions. In real life, such outcomes are observable; there is evidence that observing others’ risky real-world behaviors, such as smoking or drug use, increases the likelihood of adolescents to adopt these behaviors themselves ( Clark and Lohéac, 2007 ; Liu et al., 2017 ). This can reasonably be explained using social motivation models, if adolescents anticipate peer approval. It can also be explained with reward sensitivity models when assuming that the rewarding properties of risky behaviors (smoking) themselves become subjectively more rewarding in this social context.

In sum, experimental results from paradigms in which participants observe the choices of others are sometimes more consistent with the social motivation model, and sometimes more consistent with reward sensitivity. Paradigms designed for testing distraction models when observing others are underrepresented, so their pertinence here cannot yet be sufficiently evaluated. As such, which verbal model family best accounts for adolescent behavior when they observe others remains unclear.

Being Observed

When a decision maker is observed by another individual, risk-taking also sends a social signal to the observer ( Baker and Maner, 2009 ). For instance, adolescents can show how “cool” they are by taking extreme risks, or signal that they are or want to be part of a group by mimicking its members’ risk-taking behavior. Thus, if adolescent behavior in peer contexts is sending a social signal to their peers, their beliefs about the risk-norms of observing peers should impact their behavior. In line with this, one study found that exposing teenagers to risk-accepting peers increased their risky driving while exposure to a risk-averse peers did not ( Shepherd et al., 2011 ). Further, there is evidence that risk perception and understanding of social norms are important predictors of adolescent risky driving ( Carter et al., 2014 ). Social motivation models can therefore explain increased risk-taking in paradigms when participants are being observed.

However, even without assuming complex social motivation, behavior change in a social context was traditionally explained with social facilitation theory ( Zajonc, 1965 ), which foreshadowed both reward sensitivity, and distraction models by one principled observation: Being observed induces arousal.

The reward sensitivity model suggests that arousal leads to altered reward processing, making risk-taking more appealing. Indeed, most developmental studies of how being observed impacts risk-taking report an increase in the number of risky choices made by adolescents in social contexts ( Gardner and Steinberg, 2005 ; Chein et al., 2011 ; Smith et al., 2014 ; Somerville et al., 2018 ). In the context of social facilitation theory this increase in risk-taking can be seen either as facilitation, for example by increasing explorative behaviors and socially acceptable risk-taking, or impediment, when the risks are illegal and dangerous ( Duell and Steinberg, 2019 ). In one remarkable neuroimaging study along these lines ( Chein et al., 2011 ), found evidence for the reward sensitivity model. The presence of another person increased activity in the ventral striatum when adolescents received rewards, as compared to a solitary reward condition. This was true for adolescents but not for adults.

However, in another variant of social facilitation theory ( Sanders et al., 1978 ), social arousal is thought to result in distraction from the task at hand, thus mostly resulting in detrimental or sub-optimal behavior. In fact, there is evidence that arousal leads to decreased cognitive control, which results in more distracted behavior in decision-making tasks ( Starcke and Brand, 2012 ). There is also evidence that distraction accounts for typical adolescent behavior in some experimental paradigms. For instance, Dumontheil et al. (2016) demonstrated reduced reasoning abilities in adolescents when monitored by peers. Similarly, another study found that adolescents who showed poor conflict monitoring in an emotionally arousing Stroop task also turned out to be risky drivers in a driving simulator ( Botdorf et al., 2017 ).

Consequently, changes in risky choice while being observed could be the result of the motivation for social signaling, of arousal-based reward sensitive decisions, or distraction, and each of these three processes possibly has a different developmental trajectory. Merely observing an increase in risky decisions in adolescents seems insufficient to specify which underlying psychological process is most relevant.

In sum, different studies have emphasized different models and found results in favor of each. This holds for paradigms when adolescents are observing others and even more for paradigms in which they are observed. These mixed results may be due to the fact that each study has used different experimental paradigms with large variations of the key variables (e.g., known risk vs. uncertainty, best friend vs. unknown peer) and most studies do not directly compare different social contexts in order to identify if they are subject to different psychological processes (but see Somerville et al., 2018 ). Another reason for the diversity of experimental findings, which can also be attributed to variations in key variables, is that studies likely differ in their affective content. For instance, the affective content of a study on social influence which only uses information about choices of strangers who are not currently present is fundamentally different from a study wherein social influence is examined by looking at changes in behavior in the presence of a close friend. The distinction between affectively “hot” and “cold” contexts is a useful heuristic to understand adolescent risk-taking. There is evidence that adolescents make more risky choices in “hot” contexts. Notably, reward sensitivity and distraction models explain behavior change via affect (arousal) as well ( Blakemore and Robbins, 2012 ; Rosenbaum et al., 2018 ). In order to comprehend adolescent socio-emotional development, we need to better understand how affect and social processing interact and impact each other. We argue that the specificity provided by formal modeling might help to disentangle these important components in developmental research, similar to the field of computational psychiatry ( Montague et al., 2012 ; Huys et al., 2015 ; Jolly and Chang, 2018 ).

However, before further elaborating on the benefits of formal models in developmental research we first want to pay credit to the neuroscience of adolescent development. Neuroimaging studies may provide better clues to what extent different processes underlie behavior. In addition, it may be possible to generate more specific hypotheses about which psychological processes are involved based on the localization of neural activation.

Social Influence and Brain Development

Most verbal models of adolescent social influence are inspired by recent findings from developmental neuroimaging. Here we will review some of those findings and indicate to what extent they support existing models. Given that neural activation is a more direct reflection of the processes underlying behavior, neuroimaging may be instrumental to identify which process is most relevant in which context.

Adolescent social motivation models are supported by findings about the development of a network of brain regions associated with social cognition. This network, sometimes subsumed as the “social brain,” continues to develop during adolescence ( Mills et al., 2014 ). The most prominent regions of this network are the temporo parietal junction (TPJ), the posterior superior temporal sulcus (pSTS), the anterior temporal cortex (ATC), and the medial prefrontal cortex (mPFC). When reasoning about others, the social network seems more active in adolescents than in adults or children ( van den Bos et al., 2011 ). Further, in a study by Somerville et al. (2013) observed by others resulted in increased mPFC activity in adolescents. However, activity in these regions is not unique to social processing. For instance the same study found an adolescent increase in connectivity of the mPFC with striatal brain regions, which are relevant for processing rewards. Further, the mPFC itself is also involved in basic reward processing ( Harris et al., 2007 ; Silverman et al., 2015 ). Taken together, the increased mPFC activity when being observed can also be interpreted as supporting the reward sensitivity model.

Neural correlates of the role of adolescent reward sensitivity in non-social contexts were recently examined in a meta-analysis ( Silverman et al., 2015 ). This study estimated an increased likelihood of activation in adolescents within a broad range of regions associated with reward processing. These comprise the ventral and dorsal striatum, subcallosal cortex, insula, and amygdala as well as the anterior cingulate cortex (ACC), the posterior cingulate cortex (PCC), and the paracingulate region and the medial prefrontal cortex (mPFC). One study found increased activity in the ventral striatum when adolescents where taking risks in a social but not in a solitary context, whereas this activity difference was not found in adults ( Chein et al., 2011 ). These results are evidence in favor of the reward sensitivity model, but there are multiple possible interpretations. For instance, increased reward related neural activity could either be the result of altered reward perception or of an orthogonal, social value of conforming to a norm. Both social and non-social value is represented in the striatum ( Ruff and Fehr, 2014 ); both mechanisms can lead to more risky behavior in certain tasks.

Distraction models emphasize the development of the lateral prefrontal cortex (lPFC) and the inter parietal sulcus, which make up the main regions of the cognitive control network. Studies based on the distraction model consistently found increased IPS activation during cognitive control in adolescents, whereas lPFC findings were mixed ( Dumontheil, 2016 ). One study investigating the effects of social context on neural processing while performing a relational reasoning task found that adolescents recruited this cognitive control network more strongly than adults when an audience was present, while performance changed in a similar magnitude for both age groups ( Dumontheil et al., 2016 ). This result also allows for multiple interpretations. Adolescents may be more distracted, but on the other hand it may also be that they exert more control to counteract their distraction, and thus stay on par with adult’s behavior. The fact that they exert more control could potentially be the result of an increased motivation to perform well while observed by others.

In summation, we have seen that all verbal models are supported by neuroimaging research. Different models emphasize the development of different brain networks, but these networks often overlap with respect to functional and structural components. As long as a one-to-one mapping between cognitive and neural processes is not given, it is not justifiable to make the reverse inference about the presence or absence of a cognitive process purely on the basis of observed, or unobserved neural activity ( Poldrack, 2006 , 2011 ).

We do not wish to discredit the existing studies on neural correlates of adolescent peer influence; On the contrary, we believe that these are excellent and well-designed neuroimaging studies. In combination with appropriate experimental control conditions, reverse inference is valid and insightful ( Hutzler, 2014 ). However, experimentally isolating a cognitive process becomes exponentially difficult when the processes in question increase in complexity. Different attempts have been suggested to attenuate the issue, such as large scale brain decoding ( Poldrack, 2011 ; Yarkoni et al., 2011 ), using functional localizers ( Saxe et al., 2006 ), and formal modeling ( Marr and Poggio, 1976 ; Montague et al., 2012 ; Stephan et al., 2015 ; van den Bos and Eppinger, 2016 ; Hauser et al., 2018 ). None of these strategies will completely solve the problem of reverse inference, however, each may increase our confidence in reliably identifying the neural correlates of a particular cognitive processes. This article is motivated by the advantage of formal models; in what follows, we will illustrate how verbal models of social influence in adolescence might be translated into formal ones.

Formal Models of Social Influence

Here we demonstrate how the three verbal models about adolescent socioemotional development which we introduced earlier can be formalized as variations of expected utility models. We then show that model comparison can be used to infer underlying social mechanisms. The rationale behind formal modeling of cognition is that in order to identify if behavior is consistent with a proposed cognitive process, we need to formulate algorithms that represent the process mathematically. Comparing the behavior of the algorithms with actual behavior observed in participants can subsequently be used to quantify support for the hypothesis which is represented by the algorithm. In this section, we aim to translate verbal models of adolescent development into formal ones. However, current models often lack the details required in order to be directly translated into formal models. To formalize the models, we have therefore made several assumptions rooted in expected utility theory. The model space that we present here is not exhaustive. Nevertheless, the current framework illustrates how formal modeling can be used in developmental science, and provides a strong starting point for developing more elaborate models. More importantly, it enables precise discussions on which models are favored by existing experimental data. To formalize models of adolescent decision making First, we address how risk seeking behavior is understood within the expected utility framework in order to familiarize the reader with its’ assumptions. Then we extend these models with parameters that can be read as social sensitivity, reward sensitivity, and distraction. This finally enables us to test models of adolescent development against one another, even within the same experiment.

Expected Utility

The first assumption of expected utility theory is that people have a subjective experience of objective rewards. For instance, the first dollar someone ever earns is worth more to them than the hundredth. The change in wealth from nothing to $1 feels different from the change in wealth from $99 to $100. This transformation of objectively equal values ($1 in both cases) into a subjective utility is often modeled by a power function borrowed from psychophysics ( Helmholtz, 1896 ), where it is used to describe the non-linear relationship between subjective psychological experience of a stimulus intensity and the objective physical intensity of the stimulus:

Where V denotes the objective value of a reward and ρ determines the convexity of the utility function ( Figure 1 ). Often times this parameter is referred to capturing “outcome” or “reward sensitivity” of an individual ( Kellen et al., 2016 ). When considering risky choices rewards are not certain; they occur probabilistically. The subjective utility of a probabilistic reward is then simply described as:

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Figure 1. Verbal models of social influence during adolescence, and how they map to our taxonomy of formal models.

where p denotes the probability of the reward. Note that in more elaborate models, such as cumulative prospect theory, the probability itself is also transformed to a subjective probability weight ( Tversky and Kahneman, 1992 ). Although this would allow for even more detailed insights in developmental differences in risky behavior ( Engelmann et al., 2012 ), we do not further consider subjective probability here, as it would exponentially increase our model space and thus not serveour purpose.

When individuals are repeatedly presented with the same choice options, their decisions will most likely differ from oneanother. Consequently, we need to account for this probabilistic nature of choice in a model of behavior. To achieve this, a model for choosing between two rewards feeds the difference between reward utilities into a sigmoid function, through which we obtain an estimate of the probability that a decision maker chooses one option over another

Here, τ accounts for individual differences in choice sensitivity. The smaller τ the less sensitive the decision maker is to the expected utility differences (and the more random the choice pattern appears). We now turn to examine how different models of social decision making can be represented within this framework.

Modeling Social Influence

In our earlier example, we used the subjective value of objective monetary amounts as the key variable for decision making, but there is ample evidence that people also attribute utility to social outcomes such as fairness ( Fehr and Schmidt, 1999 ) and social status ( van den Bos, 2009 ). Furthermore, there is evidence that humans integrate value information from social and non-social sources into a common currency when making a choice (see Ruff and Fehr, 2014 , for a review). Consequently, the expected utility framework can be extended to include social rewards and represent social behavior.

Social Sensitivity

Social rewards, such as belonging or expected status gains, can add to the expected utility associated with a non-social decision, because the prospects of social and non-social rewards are combined by the brain when making a choice ( Ruff and Fehr, 2014 ).Within expected utility theory, the changed valuation of an option due to the presence of social information can be expressed as a single parameter that shifts subjective utility. For example, if we consider a typical experiment where there are two options, a relatively safe option and a risky option (defined by outcome variance differences). A social signal, for instance seeing that a peer chose the risky (safe) option, contributes to the utility of the risky (safe)option, while the expected value of the choice option and reward sensitivity remains the same ( Chung et al., 2015 ). This can be implemented with a single additional parameter:

where ψ corresponds to the impact of social information on risky and safe choice options. We call this model “symmetric social influence model.” The larger ψ the more likely the participant is to move into the direction of the social information (see Figure 2A ).

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Figure 2. Two utility functions which are used to model reward sensitivity and risk-taking. The x axis depicts the expected value of potential choice options. The y axis shows the subjective utility of these expected values given different reward sensitivity parameters. (A) A convex utility function generated by ρ = 1.7. The difference between reward magnitudes is subjectively amplified, which makes it more attractive for the individual to take risks in order to obtain higher rewards. (B) A concave utility function generated by ρ = 0.3. Risk aversion occurs here because potential rewards are compressed, therefore more similar to each other and in turn it will be less attractive to take a risk in order to obtain the higher reward. The black lines illustrate that while the difference in expected values is equal in both graphs, the difference in subjective utility of these options is smaller in the right figure. Axis ticks and labels are not shown to, to emphasize the relative, not the absolute difference as exponential functions scale very differently.

It is likely that social information has asymmetric effects on behavior depending on whether social information favorsrisk aversion or risk seeking. For instance, Braams et al. (2019) showed that risky advice had less impact than safe advice. This can be captured by adding two independent parameters to the utility function that vary depending on whether social information favors safe or risky choices (see Figure 2B ).

We call this model “asymmetric social influence model.” Note that the precise interpretation of ψ depends on the specifics of the experiment. In an experiment where the participant is observed it could represent the expected value of gaining status by taking more risks. In an experiment where the participant observes, social information can reduce the participants uncertainty about what to choose, which will then be reflected in ψ and in yet another experiment, Ψ can represent the value attributed to conforming to the behavior of others (e.g., status vs. belonging motivation). In addition, such a framework offers insight in how different aspects of the outcomes are weighted (e.g., money vs. social gains).

Reward Sensitivity

Developmental theories on social impact that focus on imbalance suggest that in a social context, rewards are valued more by adolescents because the socially induced arousal triggers reward-processing brain regions ( Chein et al., 2011 ). Reward sensitivity is a basic feature of expected utility models; it is governed by parameter ρ (see Equation 1). This parameter has already been used to characterize individual and developmental differences in risk attitudes (e.g., Blankenstein et al., 2016 ; van den Bos and Hertwig, 2017 ). To capture changes in reward sensitivity due to social facilitation one can add a parameter ω to the “reward sensitivity” part of the utility function:

The larger ω the more risk seeking an individual becomes (see Figures 1, 2C ). This equation will henceforth be called “reward sensitivity model.” In our reading of verbal reward sensitivity models, ω will never be smaller than 0 given that it is the expectation that is there is an increase, not a decrease, in risky behavior due to arousal.

Distraction

Other work emphasizes that arousal in social situations creates distracting goal conflicts, especially for adolescents ( Dumontheil, 2016 ; Dumontheil et al., 2016 ; Botdorf et al., 2017 ; Breiner et al., 2018 ). For choices that are value- or preference-based, it is hard to judge whether a decision results from distraction or inattentiveness; there is no objectively correct benchmark to evaluate correct and incorrect responses. However, formal modeling provides the means of unmasking choice stochasticity unique to social contexts that could otherwise be falsely interpreted as an increase or decrease in risk taking. Distraction or inattentiveness would lead to an increase in choices that are less determined by expected value. In decision models this kind of behavior is often captured by a “trembling hand” choice rule ( Loomes et al., 2002 ). This rule modifies the choice function by adding a fixed probability that the individual does not use expected utility to guide their choice, but rather chooses randomly. To capture this increase in distraction we can estimate how this probability of choosing randomly increases in the social context:

where a larger ζ indicates more random behavior. We will refer to this equation as the “social distraction” model. Note that more random behavior means an increase in risk taking when one would normally show risk averse behavior, and vice versa (see Figure 2D ).

Model Predictions

These formalizations of the different psychological processes involved in social influence make distinguishable predictions ( Figure 3 ). Only the social influence models clearly predict that behavior will shift in a way that is dependent on the social information content (e.g., other advice is safe or risky), or the beliefs of the subject (e.g., believe the norm is safe or risky). In contrast, for reward sensitivity or distraction models, the social context has a unidirectional main effect on behavior. The fact that the models can generate different patterns of behavior is in itself no proof that these models are actually distinguishable and suitable for model comparison. For this we need to run simulations as well as model and parameter recovery analyses in the context of specific experimental settings ( Palminteri et al., 2017 ), which we will do below.

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Figure 3. Predictions of the formal social models. The x -axis shows the difference in expected value of two choice options. The y axis shows the probability that a decision maker would choose the risky option. The horizontal line indicates the chance level for binary choice. The choice probabilities shift as a function of social information. Top panel: Predictions of models that take the content of social information into consideration. (A) Symmetric social influence in Eq. 4. Risky and safe social information impact choice equally. (B) Asymmetric social influence of Eq. 5. In this model, risky and safe social information can impact choice differentially. Bottom panel: Predictions of models that do not take the content of social information into consideration. (C) A reward sensitive decision maker (Eq. 6) would always be more likely to choose risky in a social context. (D) A distracted individual’s choices (Eq. 7) would be closer to chance in a social condition, even when the differences in expected values are extreme.

Simulation Study and Model Quality

To assess the quality of our formal models, we first simulated decisions on a set of risky gambles with varying expected value, based on all outlined models. We explicitly included the standard expected utility model without any social parameters (Eq. 2), to control for the possibility that expected utility is itself flexible enough to describe a wide range of choices. We simulated decisions in a classic economic paradigm that requires repeated choices between a probabilistic lottery with a high reward and a non-probabilistic small reward. Lotteries combined values 8, 20, and 50 (Arbitrary Units) with winning probabilities 0.125, 0.25, 0.375, 0.5, 0.675, and 0.75. The safe reference always had an expected value of 5. These values resemble those used in Blankenstein et al. (2016) . Social information provided in the simulations consisted of the choices of one risk seeking subject in Blankenstein et al. (2016) . For each social influence model, agents were divided into 12 different groups based on the distributions used to sample the parameters ψ or which represent behavior change in the face of social information in a given model (see Table 1 for details). Reward sensitivity, ρ and temperature, τ were sampled from the same distributions for all individuals, with sufficient statistics ρ∼ N (μ = 0.4,σ = 0.3) and τ∼ N (μ = 0.8,σ = 0.1). For each group and model, we simulated 50 individuals, resulting in a total of 5 ∗ 12 ∗ 50 simulated subjects that responded to 432 choice problems, 144 of which contained risk seeking social information, 144 risk averse social information which was generated by inverting the choices in the risk seeking condition and 144 featured no social information. To summarize, we modeled the behavior of subjects over a range of variables of risk- and social preferences and simulated how they would respond to different choice problems in the presence of social information. We then investigated to what extent we could correctly identify the underlying data generating models, by fitting all models to the responses we generated.

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Table 1. Characteristics of the simulations used for model and parameter recovery.

Model and Parameter Recovery

We evaluated all models with regard to their fit to the data we had previously generated. This enabled us to check whether our analysis was suitable to correctly identify the data generating model. That is, if successful, model fitting and comparison would indicate that the best fitting model was the one we used to generate the data. Only then can one confidently use these models to test specific hypotheses ( Palminteri et al., 2017 ). We judged the fit of all five models given the simulated data by consulting the deviance information criterion (DIC). Lower DIC values indicate better model fit. The rule of thumb cautiously introduced by Spiegelhalter et al. (2002) is to treat DIC values higher than 3–7 relative to a better fitting reference model to be considerably less supported by the data.

It is possible that different parameter values of a model result in the same pattern of behavior. To rule out the possibility that our models are “sloppy” in that respect, we correlated the generative parameter values with the mean of the posterior parameter distribution which we obtained by inverting the generative model on itself. A high correlation between the simulation parameters and the parameter estimates obtained from inverting the data generating model on itself is indicative that we can approximate the “true” parameter values well, when inverting the model on human choices.

Fitting Hierarchical Bayesian Models of Social Influence

We formulated the models introduced above in a hierarchical Bayesian way. This was advantageous because individual parameters could be pulled from group specific hyper distributions, which made us more sensitive to identify differences between groups and reduced outliers that often occur using frequentist fitting procedures. In our case, we drew parameters form hyper distributions for each group separately, specifying the same prior for each age group (graphical model and priors in the supplement). Non-centered parametrization was used to effectively sample subject-level parameters from the hyper distributions ( Betancourt and Girolami, 2013 ). We obtained posterior parameter distributions using the No-U-Turn-Sampler implemented in Stan ( Carpenter et al., 2017 ). For each model, we used 6,000 iterations of four parallel chains each and no thinning. The first 1,000 samples were discarded as warmup.

The results of our analyses indicate a good model and parameter recovery (see Figure 4 ). However, not all models performed equally well. While all Markov chains converged as indicated by the Gelman Rubin statistic ( Gelman and Rubin, 1992 ) and most of the parameters could be recovered reliably, the trembling hand error term ζ of the social distraction model was not recovered very well (0.24 on the diagonal). Additionally, ζ was negatively correlated with the temperature parameter of the choice function ( r = −0.6). Functional attribution to either of these parameters should be made with caution in case the social distraction model is best descriptive of the data.

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Figure 4. Results of the model and parameter recovery. (A) Confusion matrix for model recovery. Each cell depicts the frequency with which each model is best predictive for data generated under itself (columns) and inverted by itself and all other models (rows). Elements that diverge from the diagonal are evidence that one model is at danger to be “confused” with another one. The four panels on the right show the parameter recovery as correlation between the parameters used for simulation (columns) and those obtained by inverting the model (rows) for our different social influence models. (B) The symmetric social influence model, (C) the asymmetric social influence model, (D) the reward sensitivity model, and (E) social distraction model.

Applying the Models Synthesizes Seemingly Divergent Experimental Results

Having established that our proposed formal models and their parameters were recoverable, we applied the formal social influence, reward sensitivity and distraction models to data of two published studies, in order to quantify to what extent the studies support either model. Both studies investigated social influence when adolescents observed social information as they chose between different monetary lotteries ( Blankenstein et al., 2016 ; Braams et al., 2019 ). Using our formalized versions of models on social influence in adolescent risk taking, we investigated how well either study supported social information, reward sensitivity or distraction models. Both studies provided the participants with safety- and risk-promoting social information. The studies investigated how explicit information about another person’s choices changed risk-taking behavior in monetary lotteries and how this change in risk-taking was related to the participants’ developmental stage. The combined age range of both studies was 10–26. The first study focused on adolescent reward sensitivity and reported that social impact on risk-taking decreases with age ( Blankenstein et al., 2016 ). The other focused more on adolescent social motivation and found that social impact for safe behavior was strongest in adolescence ( Braams et al., 2019 ). Notably, these two studies used very similar paradigms but report results in line with different verbal models of adolescent risk-taking in social contexts. Below we will re-analyze both studies and show that formal model comparison can synthesize these seemingly divergent explanations. Our re-analysis was restricted to these two studies because these studies are so similar which made a straightforward showcase for the benefits of formal modeling.

In both datasets, we compared the formal models via DIC. The experimental paradigms included risky choices where the probability was known, and ambiguous choices where the exact probabilities where not known. For sake of simplicity, we have currently ignored the ambiguous trial types in the main manuscript. However, we believe that the discussion of risk, ambiguity or even experience-based choice in relation to adolescent risk-taking is very important, but beyond the scope of the present paper [but see Rosenbaum et al. (2018) for review]. Thus, in this articles’ Supplementary Material we report how we adjusted the formal models to include an ambiguity attitude parameter ( Tymula et al., 2012 ; van den Bos and Hertwig, 2017 ) and repeated all analyses with expected utility and ambiguity models. The main results of the model comparison remained the same (see Supplementary  Material ).

For inference on age trends in the best fitting models’ parameters, we used Bayesian general linear models, implemented in the rstanarm package ( Stan Development Team, 2018 ) utilizing rstanarm’s default priors. The age predictor was binned to represent pre- (age < 13), early- (age 13–16), late- (age 16–19), and post-adolescent (age > 19) groups. To test linear and quadratic age trends we constructed orthogonal regressors using R’s poly function. We subsequently inverted the quadratic age predictor, so that the beta estimates were more positive, when its contribution to the dependent variable increases. For each regression, we ran 3 chains with 30,000 samples each and set a warmup of 1,000 samples. Convergence of the chains was inspected by consulting stan’s implementation of the Gelman Rubin statistic ( Gelman and Rubin, 1992 ). Generally, we report the mean of the posterior and the two-sided 95% credible intervals (CI) around each mean. We treat the contribution of a predictor as negligible if the credible interval of the regression weights includes a zero.

Experiment 1: Reanalysis of Blankenstein et al. (2016)

Blankenstein et al. (2016) tested n = 157 participants aged 10–26. In this study, participants were asked to choose between a risky gamble and a safe option on 216 trials. In order to investigate susceptibility to peer influence, Blankenstein et al. (2016) programmed a virtual agent very prone to risk-taking and showed its choices to the participants prior to their choice in half of the trials. Note that this agent was very risk-taking on average, but sometimes chose the safe option as well. The probabilities and values associated with the gambles were presented as wheels of fortune ( Ernst et al., 2004 ) and were the same as the ones we used for our simulations. A full combination of gain values and probabilities resulted in 24 unique trials. The authors reported an overall increase in risky choices in the social condition; the increase was most pronounced in youngest participants and linearly diminished with age. The original analysis was motivated by the reward sensitivity model. The study design and their model-based analysis focused on a change in risk attitude as measured by the reward sensitivity parameter, ρ, which we introduced earlier. However, their reported result is, in principle, consistent with all three verbal models of risk-taking under consideration in this paper. Our reanalysis goes beyond the original analysis as we specifically designed formal models to compare competing models about the nature of social influence during adolescence within the same task.

Model comparison via DIC identified the asymmetric social influence model as best fitting ( Figure 5B ). Reward sensitivity and distraction models performed considerably worse in comparison. The best fitting model replicated the behavior of participants with great accuracy ( Figure 5A ). All age groups made more risky decisions when social information was risky, and made more safe choices when social information was safe. Strikingly, and contrary to our expectations given the original article, all participants showed a greater social influence when being confronted with safety-promoting social information ( Figure 5C ). As a next step, we performed Bayesian generalized linear regressions using age and quadratic age as predictor of the social model parameter estimates. We ran separate regression analysis on ψ risk and ψ safe , treating them as separate dependent variables. We found that the older the participants, the less they took risky advice [β AgeLin = −1.5, CI = (−1.9, −1.2)]. Older participants additionally took safe advice more often [β AgeLin = 1.4, CI = (0.9, 2.0)] as compared to younger participants. We also found adolescent decrease in taking risky advice as indicated by a negative quadratic contribution of age for following risky [β AgeQuad = −0.6 CI = (−0.9, −0.2)] but no adolescent effects on taking safe advice [β AgeQuad = 0.5 CI = (−0.0, 1.1)]. In sum, participants of all ages were influenced by both safe and risky social information. In agreement with the original author’s conclusions, we found that the impact of risky social information was strongest in youngest participants. Crucially however, safe social information had an even stronger impact than risky social information in all age groups, a conclusion which was not noted in original analyses.

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Figure 5. This panel shows the results of our model comparison procedure. (A) Percent risky choice in Blankenstein et al. (2016) , by age group and conditions. Black error bars represent the bootstrapped 95% confidence interval. Next to the mean and CI of the subjects choices (black), we show simulations under the full posterior from the winning model’ parameter estimates (blue). (B) Difference in DIC fit indices for the whole modelspace, using the winning model as a reference. (C) Posterior Parameter Estimates of ψ risk (purple) and ψ safe (yellow), binned by age group. (D) Predicted probability to choose the risky option given the difference in expected value of the gambles. Colored solid lines correspond to model predictions obtained by computing the mean of subject-level parameters in each age group. Colored dashed lines denote upper and lower confidence bounds obtained by computing the standard error of the posterior mean. Transparent lines refer to subject-level predictions.

Experiment 2: Reanalysis of Braams et al. (2019)

In this experiment n = 99 participants aged 12–22 chose between risky and safe gambles on 300 trials. Similar to Blankenstein et al. (2016) , the authors were interested in the impact of social information on risky choice across development and presented subjects with computer generated decisions that participants believed were choices from other participants of the study. Other than in Blankenstein et al. (2016) , risky and safe options were both gambles with equal probabilities: there was no sure option to choose from. In both gambles, it was either possible to win a low or a high reward. Risky gambles could result in either very low or very high rewards. For the risky options, the difference between the high and low rewards varied from $3.63 to $5.51. For safer options, there was less to lose as the difference was between $0.06 and $1. The probability of winning the high reward varied with a step size of 10% from 40% up to 90%. The lotteries were presented as colored bars, with color proportions indicating the winning probability. The authors concluded that participants followed risky and safe choices of peers and that adolescents use safe more than risky social information. Such a result speaks for social motivation models. However, as seen above: drawing conclusions about mechanisms is hard without a formal model comparison. In order to be able to apply formal model comparison here, the models were adapted to reflect the conceptualization of risk as the variability in outcomes ( Weber et al., 2004 ) used in Braams et al. (2019) . Hence, the utility of one choice option in this re-analysis is described as:

while the social extensions to this model remained the same.

Model comparison via DIC again indicated, as in Blankenstein et al. (2016) , that the asymmetric social influence model fit the overall behavior best ( Figure 6B ). Again, reward sensitivity and distraction models had considerably worse fit than the models which assume that social impact depends on the content of social information. Simulating data under the obtained posterior distributions again revealed that our models could predict the participant choices well ( Figure 6A ).

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Figure 6. (A) Percent risky choice and model simulations (blue) by age group and conditions. (B) Difference DIC fit indices for the considered model space, using the winning model as a reference. (C) Mean of the posterior parameter estimates of ψ risk (purple) and ψ safe (yellow), binned by age group. (D) Predicted probability to choose the risky option given the difference in expected value of the gambles.

As before, most participants put higher weight on safety-promoting social information than on risky social information ( Figure 6C ). To judge the statistical relevance of this pattern, we performed Bayesian generalized linear regressions, again using age and quadratic age as predictors while treating ψ risk and ψ safe as separate dependent variables. We found that linear age was not a good predictor for using risky [β AgeLin = 0.0, CI = (−0.2, 0.3)] nor safe advice [β AgeLin = −0.2 CI = (−0.4, 0.0)]. However, quadratic age trends were substantial for both risky [β AgeQuad = −0.5 CI = (−0.7, −0.3)] and safe advice [β AgeQuad = 0.6 CI = (0.4, 0.8)], implying that adolescents used risky social information less and safe social information more to guide their choice. In sum we find that safe social information has a greater impact on choice than risky information, especially so during adolescence. Again, model comparison provides evidence that all age groups differentially assign weight to risky and safe social information.

It is a widespread assumption that adolescents take risks more frequently and are more sensitive to social information than members of other age groups. Why this is the case, and in which situations this occurs remain open questions despite extensive theory development and empirical research. Several verbal models of adolescent decision-making have identified elements that may play a role in increased risk-seeking behavior. Some point to high social motivation as the principle driving force of adolescent decision-making. Others emphasize reward sensitivity or increased arousal in social situations; yet others have focused more on diminished cognitive control and increased distraction in social contexts. Most of the current experimental evidence is consistent with more than one of these explanations, resulting in a handful of plausible verbal models that explain social influence in adolescent risk-taking well. Further progress requires the systematic testing of models against each other, within different social contexts ( Pfeifer and Allen, 2016 ; van den Bos and Eppinger, 2016 ). With this goal in mind, we translated verbal models of adolescent social decision-making into formal models (c.f. Figure 1 ), which make distinguishable quantitative predictions (c.f. Figure 3 ). Using simulations and Bayesian model inversion, we first demonstrated that these models can be recovered and thus can be tested against each other using a single experimental setting (c.f. Figure 4 ). We then reanalyzed two published studies investigating the development of social influence, and showed how the model-based approach can synthesize the results of two studies on social observation (c.f. Figures 5 , 6 ). Here we will discuss the implications of our findings regarding the re-analyzes and, more importantly, the general applications and limitations of the modeling approach. Additionally, we provide specific suggestions for research on social influence in adolescence.

Adolescents Are Influenced More by Safe Social Information Than Risky Social Information

Even though the reanalyzed studies ( Blankenstein et al., 2016 ; Braams et al., 2019 ) share a similar paradigm, they are different in terms of stimuli (wheels of fortune vs. bars), reward magnitudes (high vs. low), choices (risky/safe vs. low/high risk), and the source of social information (peer vs. peer/computer/non-peer). This resulted in considerable differences in the aggregate behavior of the subjects ( Figures 5A , 6A ). However, applying our models yielded similarities between the two studies which were not easily gleaned from the original articles. First, we showed that in both experiments, participants of all ages took safety and risk promoting social information into account. This is consistent with the original interpretation of Braams et al. (2019) , but not clear from the original analysis of Blankenstein et al. (2016) . Second, model comparison and the parameter estimates of both re-analyses indicated that safer social information consistently weighs stronger than risky information, especially for adolescents. We can therefore conclude that, when risk aversion is valued by peers, social information can induce safety-promoting behaviors in adolescents. This is worth emphasizing because assuming that adolescent decision-making is maladaptive or flawed is unhelpful in designing social interventions. Restrictive public interventions solely based on that notion have been at best only mildly successful in making adolescents “better” decision-makers in the past ( Albert and Steinberg, 2011 ; Rosenbaum et al., 2018 ). Mobilizing the finding that social information can favorize safe decision-making could lead to better interventions and perhaps reduce dangerous real-world risk-taking. Taken together, our results confirm a positive outlook on adolescent decision-making and add further evidence that adolescent social motivation can be used for the good ( Perkins et al., 2011 ; Liu et al., 2017 ; Telzer et al., 2018 ; van Hoorn et al., 2018 ). However, it is important to note that our conclusions are limited to paradigms where social information is passively observed; it may well be very different when applied to data of experiments where the participant was observed by others.

Computational Modeling Can Inform Experimental Design

In principle, formal models make it possible to quantify social impact in various contexts and increase the specificity of a given hypothesis, but they are no panacea. Models require well-designed experiments: the conclusions that can be drawn from model parameter estimates and model comparison depend on the experimental paradigm. For example, as previously noted, experiments where the participant is observed could lead both to unspecific arousal and also to specific social messaging by the participant (e.g., signaling they are a risk-taker to gain status). Both phenomena can lead to an increase in risk-taking, and this behavior can be consistent with all of our formal models. In order to be able to draw informative conclusions about social mechanisms, experiments need control conditions where adolescents can achieve social status by demonstrating safe behavior. Similarly, an experiment where participants only observe the risky decisions of others is by design unable to generate support for a social sensitivity model, and would likely furnish behavioral data consistent with all models, verbal or formal. The relationship between formal model parameters and experimental elements additionally allows for an unambiguous specification of the conditions needed to distinguish between models, fostering better experimental design. Model simulations can be used a priori to show whether the specific implementation of a proposed experiment can distinguish between models 1 . In other terms, although formal models cannot compensate for poorly designed experiments, they significantly contribute to the development of experimental designs that generate testable hypotheses.

Computational Models Can Help Interpret Neuroimaging Results

All theories about the nature of adolescent decision-making are supported by neurodevelopmental research using techniques like (f)MRI. However, the often-used practice of reverse inference from observed neural activity about the engagement, or the absence of a specific cognitive process is problematic ( Poldrack, 2006 , 2011 ). Formal models are helpful in order to overcome some logical fallacies associated with reverse inference ( Poldrack, 2011 ). When using formal modeling, the engagement of cognitive processes is quantified by comparing plausible process models which are subsequently fitted to observed behaviors. In the example of expected utility models, used throughout this article, formal modeling provides insight into the otherwise hidden process of subjective utility computation. Crucially, model comparison happens before regressing the winning models’ parameter estimates to measured neuronal activity. Inference can thus be made more rigorously, avoiding logical aberrations such as assuming that activity in the mPFC solely equates social motivation, whereas this activity could also reflect reward sensitivity. Additionally, the model-based approach helps the understanding of developmental processes ( van den Bos et al., 2017 ). In summation, computational modeling is useful to attenuate some issues associated with reverse inference and can lead to more detailed, process-based insights about cognitive development.

Limitations and Future Directions

Naturally the current article is not free of caveats, some of which we will discuss in the following section. Most strikingly, our results only apply to two paradigms in which people observe behavior, and thus we cannot conclude that this pattern generalizes to behavior where participants are being observed. Real-life decisions are additionally more complex than the decisions in the binary choice tasks we have highlighted here. In the real world it is rare to be presented with accurate information about outcomes and probabilities associated with choices; there are usually multiple sources of uncertainty ( Bach and Dolan, 2012 ). Although beyond the scope of the current article, there are several computational frameworks that aim at understanding behavior under different types of uncertainty. This can take different forms such as ambiguity extensions of expected utility ( Tymula et al., 2012 ; van den Bos and Hertwig, 2017 ) or Bayesian decision frameworks, which assume that social influence is stronger when individuals are more uncertain ( Toelch and Dolan, 2015 ). There has been much attention on the distinction between risk and ambiguity in the literature; both datasets reanalyzed here also originally tested age trends in attitudes toward ambiguity. We did not focus on the ambiguous trials in the main article, as our focus was on formalizing verbal models. However, there is reason to expect that ambiguity increases social influence ( Toelch and Dolan, 2015 ) which is why we repeated the same analysis using ambiguity extensions and classical expected utility models (see Supplementary Material ). This did not affect the conclusions of our model comparison. We encourage further studies that investigate if the social parameters of the models differ between risky and uncertain or ambiguous choices. Of additional note is that in real life there is not only uncertainty about what to choose, but real-life knowledge of probabilities and outcomes is acquired dynamically through experience ( Hertwig and Erev, 2009 ). Learning in dynamic environments can be modeled within the reinforcement learning framework ( Dayan and Niv, 2008 ), which can be adapted similarly to the models we proposed here in order to comprehend the development of social influence in experience-based tasks ( Behrens et al., 2008 ; Biele et al., 2011 ; Diaconescu et al., 2014 ; Bolenz et al., 2017 ; Rodriguez Buritica et al., 2019 ).

As briefly mentioned affect is another important modulator of adolescent risk-taking. In affectively arousing (i.e., “hot”) contexts, adolescents make risky decisions more often than in less arousing (i.e., “cold”) contexts ( Figner et al., 2009 ; Defoe et al., 2015 ; Laube and van den Bos, 2016 ; Rosenbaum et al., 2018 ). In fact, social facilitation theory as well as reward sensitivity and distraction models all imply that social behavior is influenced by arousal, which itself is often understood as affectively hot. Therefore, research on social influence needs to closely examine the interaction between affect and social processing. “Cold” social situations might be where the participant is merely observing others and “hot” situations might be those where the participant is being observed or interacts with others. However, we believe that a one-to-one mapping between social and affective contexts seems overly simplistic. In the future, it will be interesting to see how different processes like reward sensitivity, social motivation or distraction have different weights in different affective contexts and how strong affect mediates behavior change. From our current understanding of the literature, “hot” contexts might be best described with reward sensitivity or distraction models whereas behavior in “cold” contexts might be better described by models emphasizing social motivation. Careful experimental design in combination with formal models may delineate the importance of each process in explaining developmental changes in peer influence.

Summary and Conclusion

Adolescents are often thought to be excessive risk-takers, especially in social contexts. Since adolescents’ risky decisions constitute a major health hazard and can have long term consequences, several attempts have been made to understand the determinants of adolescent social risk-taking. Plausible verbal models of social influence in adolescent risk-taking have been formulated, but it is difficult to identify which of the proposed processes determine adolescent behavior in a particular social situation. We argue that this is because verbal models make unspecific predictions: a broad range of observations is consistent with one, or even several, verbal models. Here we make a first attempt to specify models of social influence in adolescent risk-taking by connecting the developmental literature to theories of social psychology and representing them as simple formal models. Reanalyzing two published studies on social influence in risky choice yields that adolescents, like adults, are sensitive to the quality of social information and carefully integrate it into private decisions. In both studies, safe social information had a stronger influence than risky information on adolescents’ decisions. These results add further evidence that adolescent social sensitivity can result in safe, health promoting behavior. Investigating if and how this pattern generalizes to other contexts for instance when adolescents are being observed, will be most insightful. We hope this article encourages further work on isolating the building blocks of developmental models, through harnessing the specificity of formal modeling and model comparison.

Author’s Note

SC is a pre-doctoral fellow of the International Max Planck Research School on Computational Methods in Psychiatry and Aging Research (IMPRS COMP2PSYCH). The participating institutions are the Max Planck Institute for Human Development, Berlin, Germany and the University College London, London, United Kingdom. For more information, see https://www.mps-ucl-centre.mpg.de/en/comp2psych .

Data Availability

The data and code to reproduce all simulations, figures, and model fitting in this study can be found on github at: https://github.com/NomisCiri/Social_Adolescence_Public .

Ethics Statement

For the dataset from the study in Blankenstein et al. (2016) , written informed consent was provided by the participants themselves or by a parent in the case of minors. Recruitment, written informed consent, and procedures were approved by the local ethics committee in Leiden. The study reported in Braams et al. (2019) was approved by the Committee on the Use of Human Subjects at Harvard University.

Author Contributions

SC and WB designed the research and wrote the manuscript. SC planned, performed, and visualized the data analysis.

WB was supported by Open Research Area (ID 176), the Jacobs Foundation, the European Research Council (ERC-2018-StG-803338) and the Netherlands Organization for Scientific Research (NWO-VIDI016.Vidi.185.068).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Barbara Braams, Neeltje Blankenstein, Anna van Duijvenvoorde, and Leah Somerville for sharing the data. We also thank Deborah Ain and Cassandra Visconti for editing the manuscript, remaining mistakes are our own.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01915/full#supplementary-material

  • ^ https://github.com/NomisCiri/Social_Adolescence_Public/tree/master/A_Simulations

Albert, D., and Steinberg, L. (2011). Judgment and decision making in adolescence. J. Res. Adolesc. 21, 211–224. doi: 10.1111/j.1532-7795.2010.00724.x

CrossRef Full Text | Google Scholar

Bach, D. R., and Dolan, R. J. (2012). Knowing how much you don’t know: a neural organization of uncertainty estimates. Nat. Rev. Neurosci. 13, 572–586. doi: 10.1038/nrn3289

PubMed Abstract | CrossRef Full Text | Google Scholar

Baker, M. D., and Maner, J. K. (2009). Male risk-taking as a context-sensitive signalling device. J. Exp. Soc. Psychol. 45, 1136–1139. doi: 10.1016/j.jesp.2009.06.006

Behrens, T. E. J., Hunt, L. T., Woolrich, M. W., and Rushworth, M. F. S. (2008). Associative learning of social value. Nature 456, 245–249. doi: 10.1038/nature07538

Betancourt, M. J., and Girolami, M. (2013). Hamiltonian Monte Carlo for Hierarchical Models. Available at: http://arxiv.org/abs/1312.0906 (accessed February 5, 2019).

Google Scholar

Biele, G., Rieskamp, J., Krugel, L. K., and Heekeren, H. R. (2011). The neural basis of following advice. PLoS Biol. 9:e1001089. doi: 10.1371/journal.pbio.1001089

Blakemore, S. J., and Robbins, T. W. (2012). Decision-making in the adolescent brain. Nature Neuroscience. 15, 1184–1191. doi: 10.1038/nn.3177

Blankenstein, N., Crone, E., van den Bos, W., and van Duijvenvoorde, A. C. K. (2016). Dealing with uncertainty: testing risk- and ambiguity-attitude across adolescence. Dev. Neuropsychol. 41, 77–92. doi: 10.1080/87565641.2016.1158265

Bolenz, F., Reiter, A. M. F., and Eppinger, B. (2017). Developmental changes in learning: computational mechanisms and social influences. Front. Psychol. 8:2048. doi: 10.3389/fpsyg.2017.02048

Botdorf, M., Rosenbaum, G. M., Patrianakos, J., Steinberg, L., and Chein, J. M. (2017). Adolescent risk-taking is predicted by individual differences in cognitive control over emotional, but not non-emotional, response conflict. Cogn. Emot. 31, 972–979. doi: 10.1080/02699931.2016.1168285

Braams, B. R., Davidow, J. Y., and Somerville, L. H. (2019). Developmental patterns of change in the influence of safe and risky peer choices on risky decision-making. Dev. Sci. 22:e12717. doi: 10.1111/desc.12717

Breiner, K., Li, A., Cohen, A. O., Steinberg, L., Bonnie, R. J., Scott, E. S., et al. (2018). Combined effects of peer presence, social cues, and rewards on cognitive control in adolescents. Dev. Psychobiol. 60, 292–302. doi: 10.1002/dev.21599

Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., et al. (2017). Stan : a probabilistic programming language. J. Stat. Softw. 76, 1–32. doi: 10.18637/jss.v076.i01

Carter, P. M., Zakrajsek, J. S., Shope, J. T., and Sayer, T. B. (2014). Social norms and risk perception: predictors of distracted driving behaviour among novice adolescent drivers. J. Adolesc. Health 54, S32–S41. doi: 10.1016/J.JADOHEALTH.2014.01.008

Casey, B., Getz, S., and Galvan, A. (2008). The adolecent brain. Dev. Rev. 28, 62–77. doi: 10.1016/j.dr.2007.08.003.The

Chein, J. M., Albert, D., O’Brien, L., Uckert, K., and Steinberg, L. (2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Dev. Sci. 14, F1–F10. doi: 10.1111/j.1467-7687.2010.01035.x

Chung, D., Christopoulos, G. I., King-Casas, B., Ball, S. B., and Chiu, P. H. (2015). Social signals of safety and risk confer utility and have asymmetric effects on observers’ choices. Nat. Neurosci. 18, 912–916. doi: 10.1038/nn.4022

Clark, A. E., and Lohéac, Y. (2007). It wasn’t me, it was them!” Social influence in risky behaviour by adolescents. J. Health Econ. 26, 763–784. doi: 10.1016/j.jhealeco.2006.11.005

Crone, E. A., and Dahl, R. E. (2012). Understanding adolescence as a period of social-affective engagement and goal flexibility. Nat. Rev. Neurosci. 13, 636–650. doi: 10.1038/nrn3313

Dayan, P., and Niv, Y. (2008). Reinforcement learning: the good, the bad and the ugly. Curr. Opin. Neurobiol 18, 185–196. doi: 10.1016/J.CONB.2008.08.003

Defoe, I. N., Dubas, J. S., Figner, B., and van Aken, M. A. G. (2015). A meta-analysis on age differences in risky decision making: adolescents versus children and adults. Psychol. Bull. 141, 48–84. doi: 10.1037/a0038088

Diaconescu, A. O., Mathys, C., Weber, L. A. E., Daunizeau, J., Kasper, L., Lomakina, E. I., et al. (2014). Inferring on the intentions of others by hierarchical Bayesian learning. PLoS Comput. Biol. 10:e1003810. doi: 10.1371/journal.pcbi.1003810

Duell, N., and Steinberg, L. (2019). Positive risk taking in adolescence. Child Dev. Perspect. 13, 48–52. doi: 10.1111/cdep.12310

Dumontheil, I. (2016). Adolescent brain development. Curr. Opin. Behav. Sci. 10, 39–44. doi: 10.1016/J.COBEHA.2016.04.012

Dumontheil, I., Wolf, L. K., and Blakemore, S.-J. (2016). Audience effects on the neural correlates of relational reasoning in adolescence. Neuropsychologia 87, 85–95. doi: 10.1016/J.NEUROPSYCHOLOGIA.2016.05.001

Ellis, B. J., Volk, A. A., Gonzalez, J.-M., and Embry, D. D. (2016). The meaningful roles intervention: an evolutionary approach to reducing bullying and increasing prosocial behaviour. J. Res. Adolesc. 26, 622–637. doi: 10.1111/jora.12243

Ernst, M., Nelson, E. E., McClure, E. B., Monk, C. S., Munson, S., Eshel, N., et al. (2004). Choice selection and reward anticipation: an fMRI study. Neuropsychologia 42, 1585–1597. doi: 10.1016/j.neuropsychologia.2004.05.011

Ernst, M., Torrisi, S., Balderston, N., Grillon, C., and Hale, E. A. (2015). fMRI functional connectivity applied to adolescent neurodevelopment. Annu. Rev. Clin. Psychol. 11, 361–377. doi: 10.1146/annurev-clinpsy-032814-112753

Fehr, E., and Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation. Q. J. Econ. 114, 817–868. doi: 10.1162/003355399556151

Figner, B., Mackinlay, R. J., Wilkening, F., and Weber, E. U. (2009). Affective and deliberative processes in risky choice: age differences in risk taking in the Columbia card task. J. Exp. Psychol. 35, 709–730. doi: 10.1037/a0014983

Gardner, M., and Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: an experimental study. Dev. Psychol. 41, 625–635. doi: 10.1037/0012-1649.41.4.625

Geier, C. F., Terwilliger, R., Teslovich, T., Velanova, K., and Luna, B. (2010). Immaturities in reward processing and its influence on inhibitory control in adolescence. Cereb. Cortex 20, 1613–1629. doi: 10.1093/cercor/bhp225

Gelman, A., and Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472. doi: 10.1214/ss/1177011136

Haddad, A. D. M., Harrison, F., Norman, T., Lau, J. Y. F., Kirkham, N., and Ford, R. (2014). Adolescent and adult risk-taking in virtual social contexts. Front. Psychol. 5:1476. doi: 10.3389/fpsyg.2014.01476

Harris, L. T., McClure, S. M., van den Bos, W., Cohen, J. D., and Fiske, S. T. (2007). Regions of the MPFC differentially tuned to social and nonsocial affective evaluation. Cogn. Affect. Behav. Neurosci. 7, 309–316. doi: 10.3758/CABN.7.4.309

Hauser, T. U., Will, G.-J., Dubois, M., and Dolan, R. J. (2018). Developmental computational psychiatry. Available at: https://doi.org/10.31234/OSF.IO/85PRQ (accessed May 18, 2019).

Helmholtz, H. (1896). Handbuch der physiologischen Optik. Monatshefte Für Mathematik Und Physik. 7, A60–A61. doi: 10.1007/BF01708548

Hertwig, R., and Erev, I. (2009). The description-experience gap in risky choice. Trends Cogn. Sci. 13, 517–523. doi: 10.1016/j.tics.2009.09.004

Hutzler, F. (2014). Reverse inference is not a fallacy per se: cognitive processes can be inferred from functional imaging data. NeuroImage 84, 1061–1069. doi: 10.1016/J.NEUROIMAGE.2012.12.075

Huys, Q. J. M., Daw, N. D., and Dayan, P. (2015). Depression: a decision-theoretic analysis. Annu. Rev. Neurosci. 38, 1–23. doi: 10.1146/annurev-neuro-071714-033928

Jolly, E., and Chang, L. J. (2018). The flatland fallacy: moving beyond low-dimensional thinking. Top. Cogn. Sci. 11, 433–454. doi: 10.1111/tops.12404

Kellen, D., Pachur, T., and Hertwig, R. (2016). How (in)variant are subjective representations of described and experienced risk and rewards? Cognition 157, 126–138. doi: 10.1016/J.COGNITION.2016.08.020

Kuyken, W., Weare, K., Ukoumunne, O. C., Vicary, R., Motton, N., Burnett, R., et al. (2013). Effectiveness of the mindfulness in schools programme: non-randomised controlled feasibility study. Br. J. Psychiatry 203, 126–131. doi: 10.1192/bjp.bp.113.126649

Larsen, B., and Luna, B. (2018). Adolescence as a neurobiological critical period for the development of higher-order cognition. Neurosci. Biobehav. Rev. 94, 179–195. doi: 10.1016/J.NEUBIOREV.2018.09.005

Laube, C., and van den Bos, W. (2016). “Hormones and Affect in Adolescent Decision Making,” in Recent Developments in Neuroscience Research on Human Motivation , Vol. 19, eds S. Kim, J. Reeve, and M. Bong (Bingley: Emerald Group Publishing), 259–281. doi: 10.1108/s0749-742320160000019013

Liu, J., Zhao, S., Chen, X., Falk, E., and Albarracín, D. (2017). The influence of peer behaviour as a function of social and cultural closeness: a meta-analysis of normative influence on adolescent smoking initiation and continuation. Psychol. Bull. 143, 1082–1115. doi: 10.1037/bul0000113

Loomes, G., Moffatt, P. G., and Sugden, R. (2002). A microeconometric test of alternative stochastic theories of risky choice. J. Risk Uncert. 24, 103–130. doi: 10.1023/A:1014094209265

Marr, D., and Poggio, T. (1976). From Understanding Computation to Understanding Neural Circuitry. A.I. Memos , 357. Available at: https://dspace.mit.edu/handle/1721.1/5782 (accessed September 3, 2018).

Mills, K. L., Lalonde, F., Clasen, L. S., Giedd, J. N., and Blakemore, S.-J. (2014). Developmental changes in the structure of the social brain in late childhood and adolescence. Soc. Cogn. Affect. Neurosci. 9, 123–131. doi: 10.1093/scan/nss113

Montague, P. R., Dolan, R. J., Friston, K. J., and Dayan, P. (2012). Computational psychiatry. Trends Cogn. Sci. 16, 72–80. doi: 10.1016/j.tics.2011.11.018

Palminteri, S., Wyart, V., and Koechlin, E. (2017). The importance of falsification in computational cognitive modeling. Trends Cogn. Sci. 21, 425–433. doi: 10.1016/J.TICS.2017.03.011

Perkins, H. W., Craig, D. W., and Perkins, J. M. (2011). Using social norms to reduce bullying. Group Process. Intergroup Relat. 14, 703–722. doi: 10.1177/1368430210398004

Pfeifer, J. H., and Allen, N. B. (2016). The audacity of specificity: moving adolescent developmental neuroscience towards more powerful scientific paradigms and translatable models. Dev. Cogn. Neurosci. 17, 131–137. doi: 10.1016/j.dcn.2015.12.012

Pfeifer, J. H., Masten, C. L., Moore, W. E., Oswald, T. M., Mazziotta, J. C., Iacoboni, M., et al. (2011). Entering adolescence: resistance to peer influence, risky behaviour, and neural changes in emotion reactivity. Neuron 69, 1029–1036. doi: 10.1016/j.neuron.2011.02.019

Poldrack, R. A. (2006). Can cognitive processes be inferred from neuroimaging data? Trends Cogn. Sci. 10, 59–63. doi: 10.1016/J.TICS.2005.12.004

Poldrack, R. A. (2011). Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding. Neuron 72, 692–697. doi: 10.1016/J.NEURON.2011.11.001

Reiter, A. M. F., Suzuki, S., O’Doherty, J. P., Li, S.-C., and Eppinger, B. (2019). Risk contagion by peers affects learning and decision-making in adolescents. J. Exp. Psychol. Gen. doi: 10.1037/xge0000512 [Epub ahead of print].

Rodriguez Buritica, J. M., Heekeren, H. R., and van den Bos, W. (2019). The computational basis of following advice in adolescents. J. Exp. Child Psychol. 180, 39–54. doi: 10.1016/J.JECP.2018.11.019

Rosenbaum, G. M., Venkatraman, V., Steinberg, L., and Chein, J. M. (2018). The influences of described and experienced information on adolescent risky decision making. Dev. Rev. 47, 23–43. doi: 10.1016/j.dr.2017.09.003

Ruff, C. C., and Fehr, E. (2014). The neurobiology of rewards and values in social decision making. Nat. Rev. Neurosci. 15, 549–562. doi: 10.1038/nrn3776

Sanders, G. S., Baron, R. S., and Moore, D. L. (1978). Distraction and social comparison as mediators of social facilitation effects. J. Exp. Soc. Psychol. 14, 291–303. doi: 10.1016/0022-1031(78)90017-3

Saxe, R., Brett, M., and Kanwisher, N. (2006). Divide and conquer: a defense of functional localizers. NeuroImage 30, 1088–1096. doi: 10.1016/J.NEUROIMAGE.2005.12.062

Shepherd, J. L., Lane, D. J., Tapscott, R. L., and Gentile, D. A. (2011). Susceptible to social influence: risky “Driving” in response to peer pressure. J. Appl. Soc. Psychol. 41, 773–797. doi: 10.1111/j.1559-1816.2011.00735.x

Shulman, E. P., Smith, A. R., Silva, K., Icenogle, G., Duell, N., Chein, J., et al. (2016). The dual systems model: review, reappraisal, and reaffirmation. Dev. Cogn. Neurosci. 17, 103–117. doi: 10.1016/J.DCN.2015.12.010

Silverman, M. H., Jedd, K., and Luciana, M. (2015). Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies. NeuroImage 122, 427–439. doi: 10.1016/J.NEUROIMAGE.2015.07.083

Smith, A. R., Chein, J., and Steinberg, L. (2014). Peers increase adolescent risk taking even when the probabilities of negative outcomes are known. Dev. Psychol. 50, 1564–1568. doi: 10.1037/a0035696

Somerville, L. H., Haddara, N., Sasse, S. F., Skwara, A. C., Moran, J. M., and Figner, B. (2018). Dissecting “Peer Presence” and “Decisions” to deepen understanding of peer influence on adolescent risky Choice. Child Dev. doi: 10.1111/cdev.13081 [Epub ahead of print].

CrossRef Full Text | PubMed Abstract | Google Scholar

Somerville, L. H., Jones, R. M., Ruberry, E. J., Dyke, J. P., Glover, G., et al. (2013). The medial prefrontal cortex and the emergence of self-conscious emotion in adolescence. Psychol. Sci. 24, 1554–1562. doi: 10.1177/0956797613475633

Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and van der Linde, A. (2002). Bayesian measures of model complexity and fit. J. R. Stat. Soc. Ser. B 64, 583–639. doi: 10.1111/1467-9868.00353

Stan Development Team (2018). RStan: the R interface to Stan. R package version 2.17.3. Available at: http://mc-stan.org

Starcke, K., and Brand, M. (2012). Decision making under stress: a selective review. Neurosci. Biobehav. Rev. 36, 1228–1248. doi: 10.1016/J.NEUBIOREV.2012.02.003

Steinberg, L. (2005). Cognitive and affective development in adolescence. Trends Cogn. Sci. 9, 69–74. doi: 10.1016/J.TICS.2004.12.005

Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Dev. Rev. 28, 78–106. doi: 10.1016/j.dr.2007.08.002

Stephan, K. E., Iglesias, S., Heinzle, J., and Diaconescu, A. O. (2015). Translational perspectives for computational neuroimaging. Neuron 87, 716–732. doi: 10.1016/J.NEURON.2015.07.008

Telzer, E. H., van Hoorn, J., Rogers, C. R., and Do, K. T. (2018). Social influence on positive youth development: a developmental neuroscience perspective. Adv. Child Dev. Behav. 54, 215–258. doi: 10.1016/BS.ACDB.2017.10.003

Toelch, U., and Dolan, R. J. (2015). Informational and normative influences in conformity from a neurocomputational perspective. Trends Cogn. Sci. 19, 579–589. doi: 10.1016/J.TICS.2015.07.007

Tymula, A., Rosenberg Belmaker, L. A., Roy, A. K., Ruderman, L., Manson, K., Glimcher, P. W., et al. (2012). Adolescents’ risk-taking behaviour is driven by tolerance to ambiguity. Proc. Natl. Acad. Sci. U.S.A. 109, 17135–17140. doi: 10.1073/pnas.1207144109

van den Bos, W. (2009). Better than expected or as bad as you thought? The neurocognitive development of probabilistic feedback processing. Front. Hum. Neurosci. 3:52. doi: 10.3389/neuro.09.052.2009

van den Bos, W., Bruckner, R., Nassar, M. R., Mata, R., and Eppinger, B. (2017). Computational neuroscience across the lifespan: promises and pitfalls. Dev. Cogn. Neurosci. 33, 42–53. doi: 10.1016/J.DCN.2017.09.008

van den Bos, W., and Eppinger, B. (2016). Developing developmental cognitive neuroscience: from agenda setting to hypothesis testing. Dev. Cogn. Neurosci. 17, 138–144. doi: 10.1016/J.DCN.2015.12.011

van den Bos, W., and Hertwig, R. (2017). Adolescents display distinctive tolerance to ambiguity and to uncertainty during risky decision making. Sci. Rep. 7:40962. doi: 10.1038/srep40962

van den Bos, W., van Dijk, E., Westenberg, M., Rombouts, S. A. R. B., and Crone, E. A. (2011). Changing brains, changing perspectives: the neurocognitive development of reciprocity. Psychol. Sci. 22, 60–70. doi: 10.1177/0956797610391102

Van Hoorn, J., Crone, E. A., and Van Leijenhorst, L. (2017). Hanging out with the right crowd: peer influence on risk-taking behaviour in adolescence. J. Res. Adolesc. 27, 189–200. doi: 10.1111/jora.12265

van Hoorn, J., McCormick, E. M., and Telzer, E. H. (2018). Moderate social sensitivity in a risky context supports adaptive decision making in adolescence: evidence from brain and behaviour. Soc. Cogn. Affect. Neurosci. 13, 546–556. doi: 10.1093/scan/nsy016

Weber, E. U., Shafir, S., and Blais, A.-R. (2004). Predicting risk sensitivity in humans and lower animals: risk as variance or coefficient of variation. Psychol. Rev. 111, 430–445. doi: 10.1037/0033-295X.111.2.430

Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., and Wager, T. D. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8, 665–670. doi: 10.1038/nmeth.1635

Yeager, D. S., Dahl, R. E., and Dweck, C. S. (2018). Why interventions to influence adolescent behavior often fail but could succeed. Perspect. Psychol. Sci. 13, 101–122. doi: 10.1177/1745691617722620

Zajonc, R. B. (1965). Social facilitation. Science 149, 269–274.

Keywords : adolescence, decision-making, social influence, risk-taking, expected utility, computational modeling, hierarchical bayes

Citation: Ciranka S and van den Bos W (2019) Social Influence in Adolescent Decision-Making: A Formal Framework. Front. Psychol. 10:1915. doi: 10.3389/fpsyg.2019.01915

Received: 24 April 2019; Accepted: 05 August 2019; Published: 29 August 2019.

Reviewed by:

Copyright © 2019 Ciranka and van den Bos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Simon Ciranka, [email protected]

This article is part of the Research Topic

Impact of Social Context on Risk-Taking in Adolescence and Adulthood: Neurocognitive Underpinnings

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25 Social Influence Examples

social influence examples and definition, explained below

Social influence is the process by which individuals alter their thoughts, feelings, or behaviors as a result of their interactions with people in their social groups and communities.

It is a fundamental concept in social psychology and political science, but it is also studied extensively in the psychology of marketing to explore how brands and advertisements affect people’s behaviors.

There are multiple theories of social influence, which I will explore after providing the following examples of how people are socially influenced.

Types of Social Influence

  • Conformity : Conformity occurs when we change our behaviors or beliefs to align with the norms or standards of our in-group. According to Kelman’s social influence theory (1958), conformity is driven by a desire for other people to like and accept us.
  • Compliance : Compliance refers to a change in behavior that is prompted by a direct request from another person or group. It is not as extreme as obedience (noted below) because we aren’t compelled to obey, but rather requested to comply. People comply for various reasons, such as wanting to avoid conflict, maintaining relationships, or gaining approval.
  • Obedience : Obedience occurs when an individual is influenced into ‘toeing the line’ in response to a direct command from an authority figure such as a police officer, parent, or teacher. This differs from compliance as it often involves a power differential that means we must obey or risk direct punishment, such as a fine or detention at school.
  • Peer Pressure : Peer pressure occurs when people are influenced by those around them who share similar characteristics, such as age group or background. It is most commonly associated with adolescents, although it can affect us at all ages.
  • Persuasion : Persuasion is the act of intentionally influencing someone’s beliefs, attitudes, or behaviors through the art of rhetoric (common strategies being: logos, pathos, and ethos ). We most commonly witness this in advertising and political speeches, but it may also occur during interpersonal conversation.

chris

Social Influence Examples

  • Dressing formally for an interview (Conformity): You adapt your clothing choices to suit professional norms and expectations.
  • Laughing because everyone else is laughing (Conformity): Even if you don’t understand the joke, you laugh along to feel part of the group.
  • Buying a popular brand of sneakers (Conformity): You choose the brand because it is widely accepted and popular among your peers.
  • Switching to a reusable water bottle after seeing friends do the same (Conformity): You change your behavior to match the environmentally friendly actions of your peers.
  • Taking part in a viral social media challenge (Conformity): You join in because everyone else is doing it.
  • Agreeing to donate a small amount to charity at a supermarket checkout (Compliance): You comply with a direct request, even if it wasn’t your initial intention.
  • Signing a petition because a friend asked you to (Compliance): You might not be fully invested in the cause, but you comply to maintain the relationship.
  • Attending a meeting because your boss asked you to (Compliance): Your participation is a response to a direct request.
  • Accepting a store credit card due to a salesperson’s persuasion (Compliance): You are influenced by the salesperson’s request and the perceived benefits.
  • Paying taxes (Obedience): You obey laws and regulations set by the government.
  • Following traffic signals (Obedience): You obey the traffic rules to ensure safety and orderliness on the roads.
  • Standing for the national anthem at a sports event (Obedience): You follow an established societal rule or norm.
  • Adhering to school rules (Obedience): As a student, you follow the rules set by the school administration.
  • Joining a military draft because of a governmental decree (Obedience): You are obeying a direct command from an authority.
  • Engaging in risky behavior, like extreme sports, due to group encouragement (Peer Pressure): You take part in activities you wouldn’t usually do because of influence from peers.
  • Changing your music preferences to align with your friends’ tastes (Peer Pressure): Your music choices are influenced by the preferences of your peer group .
  • Choosing a college major based on what your friends are studying (Peer Pressure): You make academic choices based on your peers’ decisions.
  • Buying a product after watching a convincing TV commercial (Persuasion): The advertisement successfully convinces you of the product’s worth.
  • Changing your opinion about a political issue after hearing a persuasive speech (Persuasion): The speaker’s arguments influence your attitude and beliefs.
  • Starting to exercise regularly after reading compelling health articles (Persuasion): The articles present persuasive arguments that influence your behavior.
  • Subscribing to a service due to a persuasive sales call (Persuasion): The salesperson’s convincing pitch influences your decision.
  • Voting for a candidate because of their convincing campaign promises (Persuasion): The candidate’s promises and rhetoric persuade you to support them.
  • Switching to a plant-based diet after watching a compelling documentary (Persuasion): The documentary’s persuasive arguments and evidence influence your dietary choices.
  • Deciding not to buy a product because of a negative review (Persuasion): The negative review persuades you to reconsider your purchase.
  • Participating in a protest because your friends are doing it (Peer Pressure): You join in because you’re influenced by your peers, even if you might not feel strongly about the cause.
  • Changing your stance on a social issue after discussing it with your family (Informational Social Influence): Your family provides new information that persuades you to alter your perspective.

Theories and Models of Social Influence

1. social comparison theory.

Social comparison theory, proposed by Leon Festinger in 1954, suggests that individuals determine their own social and personal worth based on how they stack up against others.

People tend to compare themselves to others for self-evaluation and self-enhancement, to improve their own self-concept.

This theory often breaks social comparison down into two components – upward and downward social comparison:

  • Upward social comparison : This occurs when we compare ourselves to people who are doing better than us in the social hierarchy . Generally, we are influenced by these role models because we admire them or want to emulate them, which will influence our behaviors and actions.
  • Downward social comparison : This tends to occur when we say “at least I am not as bad as that person!” This can help us to feel better about ourselves, but also might influence us not to behave in certain ways in order to avoid the bad fate of those less fortunate than us.

2. Social Impact Theory

Developed by Bibb Latané in 1981, social impact theory explores how influential groups are, depending on a range of variables.

According to this theory, the amount of influence a person experiences in group settings depends on three variables: the strength (status or power) of the group, the immediacy (physical or psychological closeness) of the group, and the number of people in the group.

  • Group Strength: Strength refers to the importance of the group in the eyes of the individual. It can be derived from various factors such as status, authority, or personal relevance to the individual. A group that is seen as highly significant or powerful will have a stronger social impact. For example, consider the influence exerted by a panel of experts in a field versus Bob from facebook. The expert panel, due to its high status and perceived expertise, will likely have a greater impact on an individual’s attitudes or behaviors than Bob from facebook.
  • Group Immediacy: Immediacy pertains to the physical or psychological closeness of the group to the individual. This can refer to actual physical proximity or emotional closeness. A group that is physically nearby or emotionally close to an individual will tend to have a larger social influence. For example, the influence of a close-knit family or group of friends with whom an individual spends a lot of time will likely be greater than that of distant relatives or casual acquaintances.
  • Group Size: The first few members of a group (who you are most proximate to you) are most influential. As a group grows, the group influence may expand overall, but with diminishing returns per added person. For example, if an individual is faced with a differing opinion from a group of two or three people, they may be likely to reconsider their stance. However, if the group size is increased to twenty, the added influence of the additional members is less impactful than the impact of the first few people alone.

3. Elaboration Likelihood Model

The elaboration likelihood model, proposed by Richard Petty and John Cacioppo, is a theory about the ways in which persuasion works.

This model suggests two routes to persuasion: the central route and the peripheral route. The central route appeals to logic, while the periperhal route appeals to emotion.

  • The central route to persuasion : This route aims to influence people by presenting them with the merits of an argument. This route is most influential on people who are highly involved in the issue and willing to expend significant cognitive load on considering their options.
  • The peripheral route to persuasion : This route aims to influence people by presenting them with superficial cues like a charming spokesperson, emotional appeals, and brand name appeals. It persuades people based on ‘feel’ rather than ‘fact’, as seen in many television advertisements.

4. Normative vs Informational Social Influence

The contrast between normative and informational social influence was presented by Deutsch and Gerard (1955).

  • Normative social influence : This is social influence that occurs when people are influenced to change their behaviors, thoughts, and actions in order to fit in and be liked by the group. The person doesn’t need to genuinely believe in the subjective norms of the group, but rather, chooses to comply in order to achieve acceptance.
  • Informational social influence : This happens when people face ambiguity and uncertainty, so they defer to the group norm as a way to seek group wisdom and consensus. Here, people conform because they believe the group collectively is better informed than them, so they defer critical thinking to the group. For example, if you’re not sure who to vote for in an election, you ask your friends to give you advice, because you trust and respect your friends’ opinions, not simply because you want to fit in with your friend group per se .

5. Kelman’s Social Influence Theory

Herbert Kelman, the father of social influence theory , identified three broad varieties of social influence: compliance, identification, and internalization.

Kelman’s ideas overlap with those of Deutsch and Gerard (1955), where compliance and identification fit into normative influence, and internalization fits into informational influence.

  • Compliance: Here, an individual is influenced by the group because they want recognition, reward, and acknowledgment from the group.
  • Identification: In this process, we are influenced because we want to develop a sense of belonging to a group. By conforming with the group, we achieve in-group status, which makes us satisfied and feel included.
  • Internalization: We are influenced into accepting and adhering to group norms because we are socialized into genuinely believing that the group has collective wisdom . Group norms are internalized and genuinely believed to be true following sustained exposure to the group. This occurs, for example, when we feel like the cultural norms of our society are the ideal.

Factors that Impact Social Influence

  • Group Size: The size of a group can significantly impact social influence. Research in social psychology suggests that as group size increases, conformity tends to increase as well. However, this is up to a certain point; once a group reaches a certain size, additional members have less of an impact on increasing conformity.
  • Group Cohesion : Cohesion refers to the degree to which members of a group want to stay in that group and feel committed to it. Groups that are more cohesive tend to have greater social influence over their members. When individuals feel a strong connection to a group, they are more likely to align their attitudes, beliefs, and behaviors with the group’s norms.
  • Culture: Cultural background can have a profound effect on how social influence operates. In individualistic cultures (like the U.S. or Western Europe), people are more likely to resist conformity and value independence . In contrast, in collectivist cultures (like many Asian cultures), conformity and group harmony may be more highly valued.
  • Status and Authority: People in positions of status and authority typically wield more social influence. This can be seen in many contexts, such as workplaces, where managers and supervisors can significantly influence the behavior of their employees. Likewise, celebrities, due to their high status, often have the power to influence public opinion.
  • Individual Differences: Individual personality traits can impact how susceptible a person is to social influence. For instance, people with high self-esteem or a strong sense of identity may be less likely to conform than those with lower self-esteem. Similarly, individuals with a higher need for social approval may be more susceptible to peer pressure. Cognitive factors, such as a person’s level of intelligence or their tendency towards critical thinking, may also affect their susceptibility to persuasion.

We all are influenced by our social groups to a greater or lesser extent. By studying theories of how influence occurs, we can learn when we are being influenced and how to best influence others. This can, on a personal level, help us to resist influence (if that’s what we want), and on a social level, learn how to best influence others (which is especially useful when we’re working in sales and marketing).

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Social Psychology and The Notion of Social Influence

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social influence essay

Social Influence and Personal Thinking

Introduction.

Human beings are social creatures and, therefore, their decisions and thinking are highly subjected to social influence. Social influence as a sociological phenomenon is the way human beings sway the beliefs, feeling, thinking, and behaviors of one another (Fabrigar & Norris, 2015). As such, personal thinking and behavior are guided by societal norms and behaviors.

This paper analyses social influence and its effects on personal thinking and behavior. In addition, the essay examines the views of some of the sociological theories such as functionalism, conflict theory, and symbolic interaction on social influence.

Society influence to personal thinking

Personal thoughts, ideas, attitudes, and behaviors are highly influenced by society. It is worth noting that social groups have established norms, which individuals try to be in line with to avoid dissonance. Therefore, personal views of what is wrong, right, acceptable, or unacceptable are based on what social groups’ norms dictate. For instance, an individual is likely to think that a new model of a gadget is trendy and appropriate, depending on what people say about it.

Areas in personal life that are affected by social influence and how they are affected

Social influence is evident in nearly all aspects of human lives. The phenomenon can be observed in major individuals’ behaviors that replicate group norms and behavior. For instance, social influence can be linked to major political or voting decisions manifested by the public. Some politicians are elected not due to their competency but due to their abilities to manipulate social influence to their advantage. Other common areas where group decision-making is apparent include fashion/style; purchase decisions; investment decisions; reaction to disasters; cultural markets, and many other day-to-day pronouncements.

Before making decisions, people are more likely to observe the people around them. Their decisions are then informed by societal norms and behaviors. In a certain study, for instance, an analysis was carried out to investigate societal influence in individual answers to some factual questions. Each of the participants had an aggregate clue on the responses given by the majority of the test partakers. The findings were interesting since the overall responses were more or less similar (Mavrodiev, Tessone, & Schweitze, 2013).

The social influence works in diverse ways and in different models. A perfect model that can explicitly demonstrate social influence is the dissonance minimization model. In an attempt to avoid dissonance and conflicts, human beings end up behaving in accordance with societal norms (Groeber, Lorenz, & Schweitzer, 2014 ).

The good and the bad of a social influence

Social influence has both negative and positive outcomes (Muchnik, Aral, & Taylor, 2013). As such, social influence can be a good thing or a bad thing. For instance, if in a certain industry, all the firms are tax and legislation compliant, a new firm is likely to follow suit and comply with government regulations. In such a case, social influence will be a good thing. In another instance, women in a certain office who make individual decisions based on group influence may have negative impacts on individuals’ financial statuses in trying to fit in.

Another bad social influence is the use of harmful substances and drugs. For instance, smoking among youth is highly facilitated by negative societal influence (Simons-Morton & Farhat, 2010).

Minimizing social influence

It is evident that social influence plays a vital role in individuals’ decision-making processes. Nonetheless, human beings are autonomous and can make individual decisions and, therefore, minimize the social influence, especially negative effects, and herd mentality. It is imperative for an individual to take time before making decisions. As such, all factors and outcomes pertinent to a decision-making process will be considered.

Functionalism and social influence

Functionalism view society as a system with many elements that are interrelated/interconnected, working in harmony while influencing each other (Mooney, Knox, & Schacht, 2012).As such, parts and element of the society work together to strike an equilibrium in the whole society.

For instance, the family is a vital element of the society that has a mandate to nurture and socialize children. It is evident that children’s way of thinking and overall behaviors are influenced by their parents or care providers.

In addition, education and schools significantly influence youths’ attitudes, thinking, and decision-making processes. Moreover, the political class and policymakers influence legislation and major regulations that guide personal thinking and behaviors. The last part of the society that highly influences personal thinking is religion.

Conflict theory and social influence

Proponents of the conflict theory claim that the society is made up of diverse groups, which always compete for power, opportunities and resources (Mooney, Knox, & Schacht, 2012). As such, individual thinking, attitude, and behavior are influenced by the conflicting elements in the society. A poor person, for instance, argues that the rich hold the wealth and resources of the society. Therefore, their attitudes and thinking will be highly influenced by the phenomenon of the rich and the poor. For instance, Karl Marx, (a key figure and a proponent of the theory) argues that poor people tend to hide under religion due the conflicting realities of life (Mooney, Knox, & Schacht, 2012).

Symbolic interaction and social influence

Symbolic interaction adopts a more comprehensive approach to social influence relative to either functionalism or conflict theory. As such, it is referred to as macro sociology since it explains social influence in advanced (institutional) levels (Mooney, Knox, & Schacht, 2012).

The proponents of symbolic interactionism argue that personal thinking, attitudes, and behaviors are influenced by definitions and meanings generated through social interaction. In addition, people get their identities and definitions of selves through social interaction. As such, an individual’s perspective of self is highly influenced by their society’s perspectives (Mooney, Knox, & Schacht, 2012).

Social influence is evident in all societies around the world. An individual’s decision-making processes are highly influenced by the people around them. The society influences individual’s thinking, attitude, and behavior. Social influence is manifested by herd mentality, which is evident in individuals’ behaviors.

Social influence has both positive and negative effects on individuals’ thinking and decision-making processes. It is prudent to get rid of negative social influence while enhancing positive aspects of social influence. An important technique of minimizing negative social influence is taking time during decision-making. Taking time gives an individual a chance to examine the negative consequences of the herd mentality and, therefore, make autonomous and wise decisions.

Social influence can be illustrated by three sociology theories, functionalism, conflicting, and social interaction theories. Functionalism emphasizes the interconnectivity of societal elements and hence the social influence. The conflicting theory, on the other hand, suggests that the differences in the society highly influences individuals’ thinking and behavior. Lastly, the symbolic interaction theorists suggest that social influence is determined by definitions and meanings obtained from social interactions.

Fabrigar, L. R., & Norris, M. E. (2015). Conformity, Compliance, and Obedience. Oxford Bibliographies in Psychology . Web.

Groeber, P., Lorenz, J., & Schweitzer, F. (2014 ). Dissonance Minimization as a Microfoundation of Social Influence in Models of Opinion Formation. The Journal of Mathematical Sociology, 38 (3), 147-174. Web.

Mavrodiev, P., Tessone, C. J., & Schweitze, F. (2013). Quantifying the Effects of Social Influence. Scientific Reports, 3 (1360), 1-6. Web.

Mooney, L. A., Knox, D., & Schacht, C. (2012). Understanding Social Problems (8th ed.). Belmont, California: Wadsworth Publishing.

Muchnik, L., Aral, S., & Taylor, S. J. (2013). Social Influence Bias: A Randomized Experiment. Science, 341 (6146), 647-651.

Simons-Morton, B., & Farhat, T. (2010). Recent Findings on Peer Group Influences on Adolescent Substance Use. Journal of Primary Prevention, 31 (4), 191–208. Web.

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Social Thinking and Social Influence, Essay Example

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The main focus of Chapter 16 (Coon &  Mitterer, 2013) is how social networks and interactions influence human behavior. The author of the below review argues that in the age of social media, interactive communication, and instant messaging, knowing how human behavior can be influenced by society and networks is extremely important.

Human Interaction in Social Context

The authors first focus on humans’ interaction with their social context. As Coon &  Mitterer (2013, p. 548) argue: “we were born into an organized society”. This indicates that every person learns and adapts to their social environment’s norms and behavior patterns. One’s behavior is determined by their position and role in the society. Being a member of a group provides individuals with a sense of belonging, and pre-determines their roles. The main dimensions of group membership, according to the chapter are group structure and group cohesiveness. One can have several in-groups (groups that they identify with) and out-groups that they observe but do not relate to. The stronger a group cohesion is the more members will feel separate from other groups. Apart from group membership, social status and social norms also determine one’s role in the society. Social status relates to one’s level of power, importance, and influence on others, while norms determine how the individual is perceived by the rest of the people.

Social Cognition

The next question the authors examine is what determines one’s social cognition of themselves and others. The main argument of this part of the chapter is that others do not only influence individuals’ behavior, but their perception of themselves and others as well. The term “social comparison” is introduced: people often check their salary, education level, appearance against others’. This leads us to the Attribution Theory, and its implications on human behavior. According to the theory, people can create assumptions of others and guess how they are going to behave in a given situation. Considering situational demands when attributing individuals behavior patterns is often automatic. As people rarely know the reasons for others’ behavior, they are likely to attribute the reasons to external factors, and this phenomenon is called the “fundamental attribution error”. The final two factors of human behavior are child rearing and media influence.

Attitudes also influence behavior. Some attitudes are acted upon, while others are not, as the person’s perception of immediate consequences suppress them. Attitudes are also influenced by other people, groups, and the society. When somebody makes a decision about whether or not to act upon their attitude, they are likely to consider how their actions would be perceived by the rest of the society. The chapter attempts to answer an interesting question: how can we measure attitudes. Social distance scales are used to measure attitudes towards groups, while attitude scales are designed to measure one’s views on a particular issue. Several groups, politicians, and advocacy groups are working on influencing and changing people’s attitudes today. The main means of changing human attitudes are persuasion, social influence, mere presence, and – the most aggressive method – brainwashing.

Attitude, Belief,  and Behavior Modification

The authors (Coon &  Mitterer, 2013, p. 556) use the below definition to describe persuasion: “any deliberate attempt to change attitudes and beliefs through information and arguments”. It is evident that persuasion provides groups, organizations, politicians, and businesses with the power to influence not only attitudes and beliefs, but also behavior. In case of business persuasion, the main behavior change to be achieved is to become a loyal customer of the company. Politicians persuade people that their programs are intended to improve the lives of citizens, and the behavior change to be achieved is to vote for the party. There are three main principles to persuasion: the person communicating the ideas should be trustworthy and likeable, appear to have nothing to gain from the audience, and being able to appeal to emotions. Many persuasive arguments are designed to reduce cognitive dissonance, through changing one’s attitude, adding consonant thoughts, changing the importance of dissonant thoughts, reducing the amount of perceived choices, and changing one’s behavior.

Social power can also impact and influence people’s behavior and attitudes. There are five different types of power used to influence others’ behavior: reward power, coercive power, legitimate power, referent power, and expert power. An example for reward power can be managers’ power to make employees work harder by offering them a quarterly bonus for hitting their target. Coercive power can be expressed by teachers who maintain order in the classroom, as they can issue detentions for those who do not follow classroom rules. Legitimate power can be used by politicians and organization leaders. Reference power is assigned to people who have managed to lead as example, and expert power is based on one’s knowledge and expertise, for example a researcher who speaks up about a social issue.

Mere presence can also impact others’ behavior. Indeed, people tend to behave different when there are others around than when they are alone. Social facilitation is present in every aspect of life: we tend to perform better when others are present. Social loafing is another phenomenon to consider: when one is not solely responsible for the outcomes of the activity or project, they are likely to work less hard. Finally, one’s personal space and its invasion can affect behavior and attitudes. Every person considers their personal space of a different size, and when interacting with others, this needs to be considered,  just like spatial norms of different cultures.

In the final part of the chapter, the authors examine group behavior and quote several studies. Group thinking has been identified as a dangerous group behavioral pattern leading to misguided decisions. In order to maintain other members’ approval, many people ignore critical thinking techniques, and are hesitant to “rock the boat”. The authors suggest that in order to avoid adverse effects of group thinking, leaders need to ensure that all members are critically evaluating the situation, and avoid revealing their personal preferences or attitudes that could influence others.

Groups and individuals can also be influenced by several well-documented and commonly used techniques, such as the “foot in the door” effect, the “door in the face” effect, the “low ball technique”, and obedience: using authority to make people conform with demands.

The last persuasion technique discussed in the chapter is “brainwashing”. This method is a “forced attitude change” (Coon &  Mitterer, 2013, p. 567), and it considered to be unethical, as the influencer has full control over the environment and messages. Some examples for brainwashing can be found within prisons where people are made to change their beliefs, or in cults that make individuals convert. Both environments are highly controlled, and messages reaching individuals or groups within the community are filtered. Through coercion (forcing others to change their    beliefs and adapt to new norms), leaders can have control over groups and individuals. On the other hand, brainwashing does not change beliefs, only attitudes.

Overall, the chapter provided an overview of different modes of attitude and belief modification, and explained how society, group dynamics, norms, and position can influence individual choices, attitudes, and behavior patterns.

Coon, D. & Mitterer, J. (2013) Introduction to psychology: Gateways to mind and behavior with concept maps. 13 Th Edition. Cengage Learning.

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The Impact of Socialization on My Life Essay

Socialization is a process of acquiring other people’s Ideas and norms providing a person with necessary abilities for building him/herself and for societal participatory. On the other hand socialization may not be normative as “it also describes processes which may or may not affect the reflexive agents, and which may or may not lead to desirable or moral outcomes. Individual views on certain issues, such as race may again be socialized within a society” (Mathews, 2002).

Socialization also prepares an individual for the roles he/she is to play, providing him with the necessary repertoire of habits, beliefs, and values, the appropriate patterns of emotional response and the modes of perception, requisite skills and knowledge. It also provides persistence and culture (Chinoy, 1961).

Conformity to socialization is the way a person tends to have the same behaviors of a group of people he or she is attached to. Conformity and obedience to authority in socialization is responsible in shaping or bringing up a morally upright person. The impacts of this can have diverse influences on a individuals in the ways of his/her living. Therefore this paper is going to discuss on the issues of the impact that my socialization in conformity and obedience to authority and how has affected my life. The paper will also show how these issues influenced my attitudes towards the general ways of life, choice of occupation, and other important aspects in my life. The paper will then conclude by highlighting on how socialization affects individuals.

My initial socialization

My first socialization came about when I was still a little kid. I started learning the outlooks, values, and measures needed off me as a member of my family and community. An example of this is when my mother used to guide me in treating other kids as equals and not to show any discriminatory remarks or any other immoral behaviors towards them. These aspects mould me into knowing that it was acceptable and in order to treat the people around me as brothers and sisters. Socialization also taught me to learn from them as they learn from me. In addition these aspects have been permanently put into my conscience as I still have these opinions to date.

Secondary, developmental, anticipatory and occupational socialization

My next step in socialization was in relatives, friends in the neighborhoods, friends at school and people who I interacted with directly. This stage comprised of schooling and learning to get conversant to the important behaviors as an individual in a small group of a bigger community.

In growing development wise my socialization comprised of ways of learning behavior in the several organizations and institution I went through that taught me how to develop my skills socially.

My anticipatory socialization on the other hand covered my social rehearsals for the future occupations that I intended to pursue and the societal relationships that would accompany them.

The choice of occupation in regards to socialization has been positive because I have passed through knowledge-based communities which have influenced the right choice of occupation and modeled my occupational requirements as well. In this capacity, and taking into consideration personal preference about profession and occupations there has been an evident enveloping social effects. “Thus, it is necessary to expand the standard view about the process of occupation choice by adding non pecuniary factors, influence of social networks and the role of information and guidance policies” (Chinoy, 1961). My choice of occupation therefore has been affected by socialization which includes family, friends, the society and economic aspects.

Re-socialization

This process has had a major impact in my life as it has been responsible for the change of my social status. Re-socialization helped me to shade my previous ways of behaviors and come up with new ones to cope up with the ever changing world. “This again occurs throughout a human beings life cycle. Re-socialization can be an intense experience, with the individual experiencing a sharp break with their past making him or her need to learn and be exposed to radically different norms and values” (Schaefer & Lamm, 1992).

Social agents

“Agents of socialization are the people and groups that influence our self-concept, emotions, attitudes, and behavior” (Chinoy, 1961). My family and friends have been on the fore front of determining my attitudes in regards to responsibility, choice of religion and determining my occupational goals. They did this through my education which is an important agent responsible for socializing people in specific values and skills in the community. This is also responsible for my choice of occupation as it shapes an individual towards that direction. They also influenced my choice of religion that is an important aspect in socialization as it makes people obedient to authority when they follow certain rules and principles of religion. My friends have also been very influential; this was brought out through peer groupings when we used to contribute to our social characteristics in the process influencing each other. It is also evident that socialization plays a major role in influencing emotions which comprise of romance and lust. These emotions are in turn responsible for marriage especially when love strikes in a social setting. In the event of such marriages the sustenance and child rearing will be based on the instilled social norms which were shaped by socializing.

The impacts of my socialization

Socialization has evidently influenced my life in the sense that it helped me conform to authority by being shaped towards the right direction from a young age. This brought me up as a morally upright person and also helped me in the selection of an occupation of choice. The realization of this was brought about by socializing with the right people who instill the right characters in individuals. On the other hand socialization can instill the wrong characters in individuals particularly when they socialize with bad characters. This is highlighted by Zimbardo (2007) who says that a good person can be changed by socialization if he/she is not in conformity with social norms. The author gives an example of “Palestine and Iraq, where young men and women become suicide bombers who were initially good people, (Zimbardo, 2007).

Therefore as shown in this paper, new inspirations are brought about by social influence which are instilled in an individual particularly when they are consistent from a young age. It is also true that social influence does not only support moral uprightness but can also produce bad social habits.

  • Chinoy, M. (1961). Socialization. New York NY: Oxford University Press.
  • Mathews, W. (2002). Society and socialization. Journal for socialization community development 24 (2), 62-69.
  • Schaefer, D., & Lamm, T (1992). Re-socialization. Brisbane, QLD: John Wiley & Sons Australia Ltd.
  • Zimbardo, P. (2007). The Lucifer Effect : Understanding how good people turn evil. New York: Random House.

IvyPanda. (2023, October 30). The Impact of Socialization on My Life. https://ivypanda.com/essays/the-impact-of-socialization-on-my-life/

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6 Example Essays on Social Media | Advantages, Effects, and Outlines

Got an essay assignment about the effects of social media we got you covered check out our examples and outlines below.

Social media has become one of our society's most prominent ways of communication and information sharing in a very short time. It has changed how we communicate and has given us a platform to express our views and opinions and connect with others. It keeps us informed about the world around us. Social media platforms such as Facebook, Twitter, Instagram, and LinkedIn have brought individuals from all over the world together, breaking down geographical borders and fostering a genuinely global community.

However, social media comes with its difficulties. With the rise of misinformation, cyberbullying, and privacy problems, it's critical to utilize these platforms properly and be aware of the risks. Students in the academic world are frequently assigned essays about the impact of social media on numerous elements of our lives, such as relationships, politics, and culture. These essays necessitate a thorough comprehension of the subject matter, critical thinking, and the ability to synthesize and convey information clearly and succinctly.

But where do you begin? It can be challenging to know where to start with so much information available. Jenni.ai comes in handy here. Jenni.ai is an AI application built exclusively for students to help them write essays more quickly and easily. Jenni.ai provides students with inspiration and assistance on how to approach their essays with its enormous database of sample essays on a variety of themes, including social media. Jenni.ai is the solution you've been looking for if you're experiencing writer's block or need assistance getting started.

So, whether you're a student looking to better your essay writing skills or want to remain up to date on the latest social media advancements, Jenni.ai is here to help. Jenni.ai is the ideal tool for helping you write your finest essay ever, thanks to its simple design, an extensive database of example essays, and cutting-edge AI technology. So, why delay? Sign up for a free trial of Jenni.ai today and begin exploring the worlds of social networking and essay writing!

Want to learn how to write an argumentative essay? Check out these inspiring examples!

We will provide various examples of social media essays so you may get a feel for the genre.

6 Examples of Social Media Essays

Here are 6 examples of Social Media Essays:

The Impact of Social Media on Relationships and Communication

Introduction:.

The way we share information and build relationships has evolved as a direct result of the prevalence of social media in our daily lives. The influence of social media on interpersonal connections and conversation is a hot topic. Although social media has many positive effects, such as bringing people together regardless of physical proximity and making communication quicker and more accessible, it also has a dark side that can affect interpersonal connections and dialogue.

Positive Effects:

Connecting People Across Distances

One of social media's most significant benefits is its ability to connect individuals across long distances. People can use social media platforms to interact and stay in touch with friends and family far away. People can now maintain intimate relationships with those they care about, even when physically separated.

Improved Communication Speed and Efficiency

Additionally, the proliferation of social media sites has accelerated and simplified communication. Thanks to instant messaging, users can have short, timely conversations rather than lengthy ones via email. Furthermore, social media facilitates group communication, such as with classmates or employees, by providing a unified forum for such activities.

Negative Effects:

Decreased Face-to-Face Communication

The decline in in-person interaction is one of social media's most pernicious consequences on interpersonal connections and dialogue. People's reliance on digital communication over in-person contact has increased along with the popularity of social media. Face-to-face interaction has suffered as a result, which has adverse effects on interpersonal relationships and the development of social skills.

Decreased Emotional Intimacy

Another adverse effect of social media on relationships and communication is decreased emotional intimacy. Digital communication lacks the nonverbal cues and facial expressions critical in building emotional connections with others. This can make it more difficult for people to develop close and meaningful relationships, leading to increased loneliness and isolation.

Increased Conflict and Miscommunication

Finally, social media can also lead to increased conflict and miscommunication. The anonymity and distance provided by digital communication can lead to misunderstandings and hurtful comments that might not have been made face-to-face. Additionally, social media can provide a platform for cyberbullying, which can have severe consequences for the victim's mental health and well-being.

Conclusion:

In conclusion, the impact of social media on relationships and communication is a complex issue with both positive and negative effects. While social media platforms offer many benefits, such as connecting people across distances and enabling faster and more accessible communication, they also have a dark side that can negatively affect relationships and communication. It is up to individuals to use social media responsibly and to prioritize in-person communication in their relationships and interactions with others.

The Role of Social Media in the Spread of Misinformation and Fake News

Social media has revolutionized the way information is shared and disseminated. However, the ease and speed at which data can be spread on social media also make it a powerful tool for spreading misinformation and fake news. Misinformation and fake news can seriously affect public opinion, influence political decisions, and even cause harm to individuals and communities.

The Pervasiveness of Misinformation and Fake News on Social Media

Misinformation and fake news are prevalent on social media platforms, where they can spread quickly and reach a large audience. This is partly due to the way social media algorithms work, which prioritizes content likely to generate engagement, such as sensational or controversial stories. As a result, false information can spread rapidly and be widely shared before it is fact-checked or debunked.

The Influence of Social Media on Public Opinion

Social media can significantly impact public opinion, as people are likelier to believe the information they see shared by their friends and followers. This can lead to a self-reinforcing cycle, where misinformation and fake news are spread and reinforced, even in the face of evidence to the contrary.

The Challenge of Correcting Misinformation and Fake News

Correcting misinformation and fake news on social media can be a challenging task. This is partly due to the speed at which false information can spread and the difficulty of reaching the same audience exposed to the wrong information in the first place. Additionally, some individuals may be resistant to accepting correction, primarily if the incorrect information supports their beliefs or biases.

In conclusion, the function of social media in disseminating misinformation and fake news is complex and urgent. While social media has revolutionized the sharing of information, it has also made it simpler for false information to propagate and be widely believed. Individuals must be accountable for the information they share and consume, and social media firms must take measures to prevent the spread of disinformation and fake news on their platforms.

The Effects of Social Media on Mental Health and Well-Being

Social media has become an integral part of modern life, with billions of people around the world using platforms like Facebook, Instagram, and Twitter to stay connected with others and access information. However, while social media has many benefits, it can also negatively affect mental health and well-being.

Comparison and Low Self-Esteem

One of the key ways that social media can affect mental health is by promoting feelings of comparison and low self-esteem. People often present a curated version of their lives on social media, highlighting their successes and hiding their struggles. This can lead others to compare themselves unfavorably, leading to feelings of inadequacy and low self-esteem.

Cyberbullying and Online Harassment

Another way that social media can negatively impact mental health is through cyberbullying and online harassment. Social media provides a platform for anonymous individuals to harass and abuse others, leading to feelings of anxiety, fear, and depression.

Social Isolation

Despite its name, social media can also contribute to feelings of isolation. At the same time, people may have many online friends but need more meaningful in-person connections and support. This can lead to feelings of loneliness and depression.

Addiction and Overuse

Finally, social media can be addictive, leading to overuse and negatively impacting mental health and well-being. People may spend hours each day scrolling through their feeds, neglecting other important areas of their lives, such as work, family, and self-care.

In sum, social media has positive and negative consequences on one's psychological and emotional well-being. Realizing this, and taking measures like reducing one's social media use, reaching out to loved ones for help, and prioritizing one's well-being, are crucial. In addition, it's vital that social media giants take ownership of their platforms and actively encourage excellent mental health and well-being.

The Use of Social Media in Political Activism and Social Movements

Social media has recently become increasingly crucial in political action and social movements. Platforms such as Twitter, Facebook, and Instagram have given people new ways to express themselves, organize protests, and raise awareness about social and political issues.

Raising Awareness and Mobilizing Action

One of the most important uses of social media in political activity and social movements has been to raise awareness about important issues and mobilize action. Hashtags such as #MeToo and #BlackLivesMatter, for example, have brought attention to sexual harassment and racial injustice, respectively. Similarly, social media has been used to organize protests and other political actions, allowing people to band together and express themselves on a bigger scale.

Connecting with like-minded individuals

A second method in that social media has been utilized in political activity and social movements is to unite like-minded individuals. Through social media, individuals can join online groups, share knowledge and resources, and work with others to accomplish shared objectives. This has been especially significant for geographically scattered individuals or those without access to traditional means of political organizing.

Challenges and Limitations

As a vehicle for political action and social movements, social media has faced many obstacles and restrictions despite its many advantages. For instance, the propagation of misinformation and fake news on social media can impede attempts to disseminate accurate and reliable information. In addition, social media corporations have been condemned for censorship and insufficient protection of user rights.

In conclusion, social media has emerged as a potent instrument for political activism and social movements, giving voice to previously unheard communities and galvanizing support for change. Social media presents many opportunities for communication and collaboration. Still, users and institutions must be conscious of the risks and limitations of these tools to promote their responsible and productive usage.

The Potential Privacy Concerns Raised by Social Media Use and Data Collection Practices

With billions of users each day on sites like Facebook, Twitter, and Instagram, social media has ingrained itself into every aspect of our lives. While these platforms offer a straightforward method to communicate with others and exchange information, they also raise significant concerns over data collecting and privacy. This article will examine the possible privacy issues posed by social media use and data-gathering techniques.

Data Collection and Sharing

The gathering and sharing of personal data are significant privacy issues brought up by social media use. Social networking sites gather user data, including details about their relationships, hobbies, and routines. This information is made available to third-party businesses for various uses, such as marketing and advertising. This can lead to serious concerns about who has access to and uses our personal information.

Lack of Control Over Personal Information

The absence of user control over personal information is a significant privacy issue brought up by social media usage. Social media makes it challenging to limit who has access to and how data is utilized once it has been posted. Sensitive information may end up being extensively disseminated and may be used maliciously as a result.

Personalized Marketing

Social media companies utilize the information they gather about users to target them with adverts relevant to their interests and usage patterns. Although this could be useful, it might also cause consumers to worry about their privacy since they might feel that their personal information is being used without their permission. Furthermore, there are issues with the integrity of the data being used to target users and the possibility of prejudice based on individual traits.

Government Surveillance

Using social media might spark worries about government surveillance. There are significant concerns regarding privacy and free expression when governments in some nations utilize social media platforms to follow and monitor residents.

In conclusion, social media use raises significant concerns regarding data collecting and privacy. While these platforms make it easy to interact with people and exchange information, they also gather a lot of personal information, which raises questions about who may access it and how it will be used. Users should be aware of these privacy issues and take precautions to safeguard their personal information, such as exercising caution when choosing what details to disclose on social media and keeping their information sharing with other firms to a minimum.

The Ethical and Privacy Concerns Surrounding Social Media Use And Data Collection

Our use of social media to communicate with loved ones, acquire information, and even conduct business has become a crucial part of our everyday lives. The extensive use of social media does, however, raise some ethical and privacy issues that must be resolved. The influence of social media use and data collecting on user rights, the accountability of social media businesses, and the need for improved regulation are all topics that will be covered in this article.

Effect on Individual Privacy:

Social networking sites gather tons of personal data from their users, including delicate information like search history, location data, and even health data. Each user's detailed profile may be created with this data and sold to advertising or used for other reasons. Concerns regarding the privacy of personal information might arise because social media businesses can use this data to target users with customized adverts.

Additionally, individuals might need to know how much their personal information is being gathered and exploited. Data breaches or the unauthorized sharing of personal information with other parties may result in instances where sensitive information is exposed. Users should be aware of the privacy rules of social media firms and take precautions to secure their data.

Responsibility of Social Media Companies:

Social media firms should ensure that they responsibly and ethically gather and use user information. This entails establishing strong security measures to safeguard sensitive information and ensuring users are informed of what information is being collected and how it is used.

Many social media businesses, nevertheless, have come under fire for not upholding these obligations. For instance, the Cambridge Analytica incident highlighted how Facebook users' personal information was exploited for political objectives without their knowledge. This demonstrates the necessity of social media corporations being held responsible for their deeds and ensuring that they are safeguarding the security and privacy of their users.

Better Regulation Is Needed

There is a need for tighter regulation in this field, given the effect, social media has on individual privacy as well as the obligations of social media firms. The creation of laws and regulations that ensure social media companies are gathering and using user information ethically and responsibly, as well as making sure users are aware of their rights and have the ability to control the information that is being collected about them, are all part of this.

Additionally, legislation should ensure that social media businesses are held responsible for their behavior, for example, by levying fines for data breaches or the unauthorized use of personal data. This will provide social media businesses with a significant incentive to prioritize their users' privacy and security and ensure they are upholding their obligations.

In conclusion, social media has fundamentally changed how we engage and communicate with one another, but this increased convenience also raises several ethical and privacy issues. Essential concerns that need to be addressed include the effect of social media on individual privacy, the accountability of social media businesses, and the requirement for greater regulation to safeguard user rights. We can make everyone's online experience safer and more secure by looking more closely at these issues.

In conclusion, social media is a complex and multifaceted topic that has recently captured the world's attention. With its ever-growing influence on our lives, it's no surprise that it has become a popular subject for students to explore in their writing. Whether you are writing an argumentative essay on the impact of social media on privacy, a persuasive essay on the role of social media in politics, or a descriptive essay on the changes social media has brought to the way we communicate, there are countless angles to approach this subject.

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Social Influence Essays

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social influence essay

Social influence has a number of meanings in psychology, it is generally used to summarise the field of social psychology. Studying "how thoughts, feelings and behaviour of individuals are influenced by actual, imagined or implied presence of others" (Allport, 1968).

Social influencedescribes how our thoughts, feelings, and behaviors respond to our social world, including our tendencies to conform to others, follow social rules, and obey authority figures. Social influence takes two basic forms: implicit expectations and explicit expectations. Implicit expectations are unspoken rules.

Social influence is the process by which an individual's attitudes, beliefs or behavior are modified by the presence or action of others. Four areas of social influence are conformity, compliance and obedience, and minority influence. Conformity (Majority Influence)

To make a first step toward formal models of social influence during adolescence, we first identify three prominent verbal models of social influence in the literature: (1) social motivation, (2) reward sensitivity, and (3) distraction.

Social influence: A cross-cultural perspective. In K. D. Keith (Ed.), Cross-cultural psychology: Contemporary themes and perspectives (pp. 549-574). Wiley Blackwell. https:// https://doi.org/10.1002/9781119519348.ch27 Abstract Culture presents a unique perspective on understanding much of the social influence literature.

Social influences are things that alter or influence an individual's feelings, conduct, opinions, or actions. Both sociologists and psychologists find this concept of great value, for example, social influence is a pivotal tool for marketing, smoking and many more. We will write a custom essay on your topic 807 writers online Learn More

Topic 1: Social Influence Essay Plans This work by PMT https://bit.ly/pmt-edu-cc Education is licensed under https://bit.ly/pmt-cc CC BY-NC-ND 4.0 Outline and evaluate Milgram's research on obedience (16 marks). Read the item below and answer the question that follows. Two psychology students were discussing the topic social influence.

The study of social influence is central to social psychology and to understanding group processes and intergroup relations. Social influence research covers a broad range of topics, from...

There are two main reason of the motivation to conform one is informational social influence and the other is normative social influence. Informational social influence is depending on other people's attitudes to gain information when a person is uncertain about what response to give because he believes that the group is right and competent.

Social Influence Essay Sort By: Page 1 of 50 - About 500 essays Social Influence And Conformity The Power behind Social Influence & Conformity The article "Social Influence on Risk Perception during Adolescence" by Lisa j.

Social influence as a sociological phenomenon is the way human beings sway the beliefs, feeling, thinking, and behaviors of one another (Fabrigar & Norris, 2015). As such, personal thinking and behavior are guided by societal norms and behaviors. Our experts can deliver a Social Influence and Personal Thinking essay tailored to your instructions

Social status relates to one's level of power, importance, and influence on others, while norms determine how the individual is perceived by the rest of the people. Social Cognition The next question the authors examine is what determines one's social cognition of themselves and others.

As a result the changed person perceives themselves to be in a relationship in the influencer, other people or society in general. Social influence has many forms and can be seen in conformity, obedience, compliance, power, sales, marketing, socialization, peer pressure, persuasion etc. According to Lisa Rashotte, social influence is defined as ...

749 Words | 3 Pages Social influence is a powerful thing that affects the behaviors, feelings and beliefs of all people. Social influence is shown through marketing, the media and daily life situations. The three main types of social influence is conformity, compliance and obedience.

Social influence is carried out at various levels - from individual to global. The phenomenon occurs when an individual is influenced by the surrounding emotions, beliefs, norms and values, leading to socialization, interaction, identification and conformity. We will write a custom essay on your topic 807 writers online Learn More

Influence by command if often found in the institution where strict adherence to law and regulation is required. A good example is the military unit; the officers have to follow strict command from the authority. Obedience as a form of social power is one sided; it does not require the consent of the other party.

Social Influences on Behavior Rhonda Hager PSY/300 June 25, 2012 Teresa Neal Social Influences on Behavior Introduction All humans' behavior is affected by social influences to some extent. The level of influence will vary from person to person, depending on the several factors, such as self-esteem, their level of self-awareness, morals, and ...

Social agents "Agents of socialization are the people and groups that influence our self-concept, emotions, attitudes, and behavior" (Chinoy, 1961). My family and friends have been on the fore front of determining my attitudes in regards to responsibility, choice of religion and determining my occupational goals.

PAGES 2 WORDS 604 Social Influence and Persuasion Social influence is believed to occur when an individual's emotions, behaviors, or opinions are influenced by others'. Compliance, identification, internalization are the three broad varieties of social influence that have since been identified.

Here are 6 examples of Social Media Essays: The Impact of Social Media on Relationships and Communication Introduction: The way we share information and build relationships has evolved as a direct result of the prevalence of social media in our daily lives. The influence of social media on interpersonal connections and conversation is a hot topic.

3354 Words | 7 Pages What are the unseen social forces that push and pull us to behave or think in a certain way? Why do we behave and interact with others in the way that we do? Research on social influence helps shed light on these invisible forces in our world that influence us.

Social Influence Essays. Attitudes and Personality Paper. A description of the differences between personality and attitude. Personality is the set of behaviors, thoughts, and emotions that can be used to describe a person's character. It is organized into five major areas: openness, conscientiousness, agreeableness, neuroticism, and ...

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  1. Justify text in SQL Reporting Services

    Is there a way of fully-justifying text in SQL Reporting Services? I've been searching around and it seems the feature is still not supported by Reporting Services, but are there any workarounds? I know this question has been asked before, but maybe progress has been made in the mean time. sql reporting-services Share Improve this question Follow

  2. SSRS Report textbox text-align:Justify

    Jan 20, 2022, 1:25 AM Hi, I have built out the SSRS Report and in that I have a textbox and I'm showing text summary with 10 lines. I was trying to find a text align to be "Justify", but i cannot find. I tried googling, to figure out a solution for text-align: justify;

  3. SQL Server Reporting Services (SSRS): How to Justify Text ...

    If justification Then ' Justify the text. Dim words As String () = line.Split (" "c) ' Add a space to each word and get their lengths. Dim word_width As Single () = New Single (words.Length - 1) {} Dim total_width As Single = 0 For i As Integer = 0 To words.Length - 1 ' See how wide this word is.

  4. SQL Server Reporting Services (SSRS): How to Justify Text (Part 2)

    SQL Server Reporting Services (SSRS): How to Justify Text (Part 2) 4. October 2017 [email protected] Microsoft Business Intelligence, Phidiax Technology, .Net (9) Left, Right, and Center. Those are the only options right? That might be how SSRS views the world, but nope...

  5. Justificar textos en Reporting Services de manera fácil y rapida

    0:00 / 17:27 Justificar textos en Reporting Services de manera fácil y rapida Algo NERD 14 subscribers Subscribe 8.2K views 6 years ago Justify text in reporting services En este video vemos...

  6. Tutorial: Aplicación de formato a un texto (Generador de informes

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  7. How to Justify Text in SSRS

    How to Justify Text in SSRS Microsoft does not support justified or letter text alignment in Reporting Services: Aspose offers a solution http://www.aspose.com/ Share Tweet Print Email Pie chart Series Label Overlapping in SSRS The report definition is not valid Report Name Extension Replacement SSRS Divide By Zero Error No Comments Yet.

  8. Justify FullJustify Text Alignment|Aspose.PDF for Reporting Services

    With Aspose.PDF for Reporting Services, you can do that easily by adding custom properties. Custom Property Name : TextAlignment. Custom Property Type : String. Custom Property Values : Justify, FullJustify. In report the code should be like the following:

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  12. Justificar un pàrrafo en Reporting Services

    No existe una forma sencilla de justificar un texto en Reporting, tienes las opciones de alinear al la izquierda, derecha y centro, pero esa funcionalidad está todavía por venir. Te animo a que crees (o votes en caso de que ya exista) una sugerencia para que MS lo tenga en cuenta para futuras versiones: https://connect.microsoft.com/SQLServer.

  13. Justificar Texto en SQL Reporting Services 2008 R2

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  14. Full Text Justification in newer SQL Server Reporting Services

    1 Answer. Sorted by: 1. There is no full justify option for text boxes, even in 'newer' versions of SSRS (I assume you mean 2012 onwards). Your only option is to use a third party product such as Aspose. Share. Follow. answered Aug 31, 2015 at 8:29.

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    Justificar texto. Buenos días amigos de la wep, ¿alguien sabe como justificar un texto en reporting? tal como se hace en word para que los margenes izquierdo y derecho aparezcan homogeneos, veo que unicamente traen los botones de alinear a la derecha, alinear a la izqquierda y centrar, el botón de justificar lo encontre lo agregue en la ...

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  17. reporting services justificar texto

    Justify text in SQL Reporting Services. Is there a way of fully-justifying text in SQL Reporting Services? I've been searching around and it seems the feature is still not supported by Reporting Services, but are there any workarounds? I know this question has been asked before, but maybe progress has been made in the mean time. reporting-services

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