Social Influence and News Consumption

Last registered on December 14, 2023
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Pre-Trial

Trial Information

General Information

Title
Social Influence and News Consumption
RCT ID
AEARCTR-0011147
Initial registration date
March 26, 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
March 30, 2023, 3:35 PM EDT

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

Last updated
December 14, 2023, 10:29 AM EST

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Carlos Andres Molina Guerra
Affiliation
Massachusetts Institute of Technolohy.
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Other Primary Investigator(s)

PI Name
Alex Moehring
PI Affiliation
Massachusetts Institute of Technology
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2023-03-12
End date
2023-07-31
Keywords
Behavior
Additional Keywords
news diet, disclosure, learning, Twitter.
JEL code(s)
C93, D72, D83, L82
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Populations in many countries have become decidedly more polarized over the last decades. Many believe that social media, which creates echo chamber-like interactions, is partly to blame. In principle, more intense communication between like-minded individuals can have two distinct impacts on political beliefs. First, individuals may receive a slanted diet of political news shared by their like-minded friends. Second, they may purposefully slant their own news consumption, and beliefs, in order to remain more in line with these friends. Despite the importance of these questions, there is little evidence for either of these two types of influences. This paper designs a unique field experiment on Twitter to separately identify both mechanisms. In our sample, politically-active individuals consume a highly slanted news diet. By varying what an individual’s social media followers see about her news diet and tracking their news consumption and sharing behavior, we test if (1) this news diet has an impact on individual behavior and beliefs; and more importantly, (2) whether individuals manipulate their news diet in order to remain more in line with their friends when they believe that their choices will be observed by these friends. This is either because they would like to signal to their friends via their news diet choices or because they are afraid of certain reactions when they deviate from a news diet aligned with their friends’ ideological position.
External Link(s)

Registration Citation

Citation
Moehring, Alex and Carlos Andres Molina Guerra. 2023. "Social Influence and News Consumption." AEA RCT Registry. December 14. https://doi.org/10.1257/rct.11147-1.1
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2023-03-12
Intervention End Date
2023-07-31

Primary Outcomes

Primary Outcomes (end points)
Our primary outcomes for the first stage regressions are a dummy equal to one if the participant shares the news diet summary (disclosing). Also, the difference between the posterior and the prior beliefs about the ideology of the peers (learning).

Our first primary outcome measures the extensive margin of whether individuals make any change to the publishers they follow. As a complementary outcome, we also look at the intensive margin (how much individuals change).

Our other set of primary outcomes is the direction of such change (whether individuals move towards/against the right, their peers, the center). When more than one publisher is followed, we based the construction of our outcomes on the average slant of the followed publishers.

We plan to use the Twitter API to monitor user activity in the account of the participants after our experiment takes place. This would allow us to understand whether potential changes made during our experiment either dissipate or exacerbate over time. The probability of the effects dissipating over time ultimately would depend on (i) the probability of an user maintaining the changes done during the experiment and (ii) the sensibility of the user to the content in her news feed (which is affected by the publishers that she might have followed). To test (i), our main outcome of interest is a dummy equals one if the user keep following the publishers $k$ weeks after the intervention (initially, we would consider $k\leq$4 and extend the window if persistence is high enough by the end of week four). To test (ii), we plan to look at change on Twitter behavior by the user (conditional on the treatment). This includes, the slant of the likes, retweets, mentions and follows of material that the user engage with $k$ weeks after the intervention (where $k$ is defined above).

Depending on the take-up rate of the follow-up survey (see Section \ref{secadditional}), we will also explore all the complementary outcomes on political knowledge, political polarization and political beliefs in this survey.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In this study, we propose an online field experiment to overcome these challenges in the context of demand for biased information. Our experiment allows us to separate between two main channels through which peers can influence an individual’s news diet and ultimately their political views and polarization: an internal one, where the news peers consume impacts the news diet of an individual through discovery or signaling quality and a external one, where individuals alter their news diets when observed by their peers.
Experimental Design Details
Randomization Method
Randomization is done in office by a computer.
Randomization Unit
Individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
7000
Sample size (or number of clusters) by treatment arms
public/private treatment is randomized 50%/50%.
information/no information treatment is randomized 80%/20%.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available
Analysis Plan

Analysis Plan Documents

Preanalysis Plan: social influence and news consumption

MD5: 1ccfdbd6e09ab1994158e6d6882cc05a

SHA1: a015a112f4d326099543663fd1f9928c72635b93

Uploaded At: March 26, 2023

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials