The Visual Narrative: The Effects of Visual Stereotypes on Social Media on Ethnic Discrimination

Last registered on February 06, 2024

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Pre-Trial

Trial Information

General Information

Title

The Visual Narrative: The Effects of Visual Stereotypes on Social Media on Ethnic Discrimination

RCT ID

AEARCTR-0011322

Initial registration date

May 09, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

May 17, 2023, 2:13 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated

February 06, 2024, 7:35 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

Germany

Region

Primary Investigator

Name

Raphael Moritz

Affiliation

University of Tuebingen

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Christian Manger

PI Affiliation

University of Tuebingen

Contact Investigator

PI Name

Kerstin Pull

PI Affiliation

University of Tuebingen

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2023-03-01

End date

2024-01-31

Keywords

Behavior

Additional Keywords

Ethnic Discrimination, Stereotypes, Social Media, Information Acquisition, Field Experiment, Shared Housing, Information Systems

JEL code(s)

C93, D83, D84, R31, J15

Secondary IDs

Prior work

This trial is based on or builds upon one or more prior RCTs.

Abstract

We conduct a correspondence test in the housing market to determine the extent of ethnic discrimination and the role of stereotypes expressed through images posted on a social media platform. Fictitious applications with a randomly assigned Turkish- or German-sounding male name are sent to vacant room ads. We randomly add a link to a social media profile to determine the effect of such personal information on callback rates. This social media profile may either foster or not foster Turkish male stereotypes. The profiles built on the profiles used in AEARCTR-0007627 and vary their content by some of them including additional visual material (photos and videos) that signal religious beliefs and cultural orientation to thus identify the role of the content of social media information on ethnic discrimination. We carefully constructed these fictional social media accounts on Instagram to make them as realistic as possible, and conducted several surveys among young people to ensure that the profiles were close to reality with a sufficient number of followers. In addition, we can approximate whether landlords or roommates visit these profiles and exploit this information using statistics on profile visits and page impressions.

External Link(s)

Registration Citation

Citation

Moritz, Raphael, Christian Manger and Kerstin Pull. 2024. "The Visual Narrative: The Effects of Visual Stereotypes on Social Media on Ethnic Discrimination." AEA RCT Registry. February 06. https://doi.org/10.1257/rct.11322-3.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2023-06-01

Intervention End Date

2024-01-15

Primary Outcomes

Primary Outcomes (end points)

Callback rates conditional on ethnicity and social media information (variation of information using stereotypical Turkish signal images).

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We use a non-matched pair randomized controlled trial (correspondence test, between-subjects design) to test for ethnic discrimination in the shared housing market in Germany. To do so, we randomly vary the name of the applicant, which signals an ethnic minority or ethnic majority. The ethnic minority (majority) is signaled by the most average (in terms of callbacks) Turkish-(German-)sounding male name from the previous study (see AEARCTR-0007627). In addition, we create four social media profiles, two with additional information signaling cultural identification and religious beliefs, which address typical Turkish stereotypes (as held by the ethnic majority), and two without (Turkish) stereotypical images, representing an average student social media profile from the previous study. The submitted applications are similar in all aspects except for the parts that (a) signal the applicant's ethnicity, (b) whether it contains a link to the social media profile, and (c) the content of the profile (2x3 design).

Update (2023-10-27): Due to a design change on the platform during the trial, we add another variation with paid premium accounts that increase the visibility of applications from premium users. Thus, in addition to randomly varying (a) ethnicity, (b) social media profile link, (c) social media profile content (with/without Turkish stereotypical images), (d) we randomly vary whether the application is sent from a premium account (2x2x3 design). With this, we aim to investigate how increased visibility of applications (due to the platform design change) affects callback rates by ethnicity, and how providing additional information (social media*with/without Turkish stereotypical images) moderates this effect – compared to applications from non-premium users with lower visibility.

Experimental Design Details

Randomization Method

Computer generated (pseudo) randomization using a computer program (using Python).

Randomization Unit

Individual level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

n/a

Sample size: planned number of observations

3,500-4,000 (Update (2023-10-27): Due to a platform design change, we add another variation (premium/non-premium) and increase the number of planned observations by roughly 800-1,200.)

Sample size (or number of clusters) by treatment arms

Assuming a 40.3% percent overall callback rate (from previous study) we will send out approximately 677 applications for each of the six treatment groups (immigrant/native*with/without stereotypical/non-stereotypical social media profile), resulting in 1,354 applications per treatment arm. Depending on the callback rate, this number may be lower or higher in the final sample.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB