Selective Exposure and Trust in News

Last registered on December 02, 2024

Pre-Trial

Trial Information

General Information

Title
Selective Exposure and Trust in News
RCT ID
AEARCTR-0014741
Initial registration date
November 01, 2024

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
December 02, 2024, 11:08 AM EST

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

Locations

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Primary Investigator

Affiliation
UCL

Other Primary Investigator(s)

PI Affiliation
Stanford
PI Affiliation
Stanford

Additional Trial Information

Status
In development
Start date
2024-11-01
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In the United States, Democrats and Republicans tend to consume different types of news, as partisans are more likely to seek out information that supports their party. This paper seeks to better understand why people tend to consume more co-partisan news. In particular, we consider two main types of explanations: people believe that co-partisan sources are more accurate and instrumentally value them more, and people have a preference to read co-partisan sources for reasons besides their instrumental value. To disentangle these hypotheses, we run an experiment in which people choose news sources when they are asked to make predictions about a salient political event, and we vary the incentives they have for making accurate predictions. When incentives increase, people may turn to sources they expect to be more instrumentally valuable, and potentially away from sources they consume for other reasons. We test this effect using real news sources like Fox News and CNN, as well as using artificially-constructed sources that exogenously vary in accuracy and slant. To isolate the channel that accuracy of news-source predictions play, we both analyze behavior when they use news sources to improve their own prediction, as well as when news sources make predictions for them.
External Link(s)

Registration Citation

Citation
Gentzkow, Matthew, Peter Robertson and Michael Thaler. 2024. "Selective Exposure and Trust in News." AEA RCT Registry. December 02. https://doi.org/10.1257/rct.14741-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We have copied text from our pre-analysis plan in the "Hidden" field below.
Intervention Start Date
2024-11-01
Intervention End Date
2024-11-05

Primary Outcomes

Primary Outcomes (end points)
Co-partisan choice: Indicator variable for whether the participant ranks the co-partisan source higher than the other two available sources.
Primary Outcomes (explanation)
We provide further information and detail our regression specification in our pre-analysis plan.

Secondary Outcomes

Secondary Outcomes (end points)
Same source: Indicator variable for whether the participant ranks the same source highest (among all three available sources) across elicitation with and without incentives.

Isolation index: Within the experiment, this is intended to measure how much selective exposure there is between Democrats and Republicans. We estimate the index using Gentzkow and Shapiro (2011).
Secondary Outcomes (explanation)
We provide further information, detail our regression specification, and discuss auxiliary outcomes, in our pre-analysis plan.

Experimental Design

Experimental Design
We have copied text from our pre-analysis plan in the "Hidden" field below.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer
Randomization Unit
We provide this information in our attached pre-analysis plan.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
4,000 participants
Sample size: planned number of observations
4,000 participants
Sample size (or number of clusters) by treatment arms
We provide this information in our attached pre-analysis plan, as well as in the experimental design section above.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
UCL Research Ethics Committee
IRB Approval Date
2024-10-24
IRB Approval Number
12439/001
IRB Name
Stanford University Institutional Review Board
IRB Approval Date
2024-11-01
IRB Approval Number
77656
Analysis Plan

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