Willingness to Tweet (2)

Last registered on October 26, 2021

View Trial History

Pre-Trial

Trial Information

General Information

Title

Willingness to Tweet (2)

RCT ID

AEARCTR-0008432

Initial registration date

October 25, 2021

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

October 26, 2021, 3:16 PM EDT

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

Locations

Country

United States of America

Region

Illinois

Primary Investigator

Name

Aakaash Rao

Affiliation

Harvard University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Leonardo Bursztyn

PI Affiliation

University of Chicago

Contact Investigator

PI Name

Ingar Haaland

PI Affiliation

NHH Norwegian School of Economics

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PI Name

Christopher Roth

PI Affiliation

University of Cologne

Contact Investigator

Additional Trial Information

Status

In development

Start date

2021-10-27

End date

2021-11-03

Keywords

Behavior, Crime, Violence, & Conflict

Additional Keywords

Twitter, social norms, social image

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

We examine how social image considerations affect participants' willingness to publicly Tweet about socially sensitive topics.

External Link(s)

Registration Citation

Citation

Bursztyn, Leonardo et al. 2021. "Willingness to Tweet (2)." AEA RCT Registry. October 26. https://doi.org/10.1257/rct.8432-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We vary the perceived social image cost associated with making a Tweet about a socially sensitive topic.

Intervention Start Date

2021-10-27

Intervention End Date

2021-11-03

Primary Outcomes

Primary Outcomes (end points)

Whether or not the participant chooses to authorize the Twitter post

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We vary the perceived social pressure associated with making a Tweet about a socially sensitive topic.

Experimental Design Details

Participants are shown an article written by Princeton criminologist Patrick Sharkey discussing the likely effect of defunding the police on violent crime and decide whether or not to (privately) join a campaign to oppose defunding the police. They are then told they will have the opportunity to schedule a post to be made on their Twitter account encouraging their followers to sign a petition to oppose defunding the police. The experiment manipulates only one word: whether the post indicates that the participant saw the article before joining the campaign, or after joining the campaign. (They are told that this post will be made public if and when we have reached survey respondents in all US counties. However, given that we are collecting fewer observations than the number of US counties, this will not happen, and thus the posts will never be made public.)

The experiment manipulates only one word: whether the post indicates that the participant saw the video before joining the campaign, or after joining the campaign. We are interested in examining whether respondents who believe that their audience will believe that they saw the video before joining -- and thus, had an "excuse" to join -- are more willing to schedule the post.

Randomization Method

Randomization through Qualtrics

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

Sample size: planned number of observations

We will ideally recruit 1000 participants. However, based on conversations with our survey provider, it may be infeasible to recruit 1000; they have guaranteed that we can recruit at least 500. Thus, we will end our collection when we reach 1000 or after seven days have elapsed (whichever occurs first). We will restrict our sample to people who pass a simple attention check (pre-intervention).

Sample size (or number of clusters) by treatment arms

250-500 treatment, 250-500 active control (see above)

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

With 500 respondents total, based on our pilot data, we will have 80% power to detect an 11 percentage point effect at the 10% level. With 1000 respondents, we will have 80% power to detect a 8 percentage point effect at the 10% level.

Supporting Documents and Materials

IRB