Political Communication on WhatsApp: Mechanisms

Last registered on January 17, 2025

Pre-Trial

Trial Information

General Information

Title
Political Communication on WhatsApp: Mechanisms
RCT ID
AEARCTR-0015208
Initial registration date
January 15, 2025

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
January 17, 2025, 7:23 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
University of Michigan

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-01-16
End date
2025-02-15
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This online survey experiment builds upon a previous field experiment (Carney, 2024), which studied the causal impact of political WhatsApp groups. The survey uses the content of messages posted to political WhatsApp groups during that study and varies the context in which the content is shared, to understand how people react to particular features of political WhatsApp messages. Participants will see a series of images of WhatsApp messages and be asked a series of questions about how they would view and respond to the message. Each screenshot will feature two messages. The messages will randomly vary in (1) whether they are attributed to a political party or an individual, (2) whether a different individual replied in agreement, disagreement, or with a neutral message, and (3) whether the chat is open to replies from other users.
External Link(s)

Registration Citation

Citation
Carney, Kevin. 2025. "Political Communication on WhatsApp: Mechanisms." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.15208-1.0
Experimental Details

Interventions

Intervention(s)
Participants will see a series of 9 screenshots of a hypothetical conversation in a WhatsApp group, each featuring two messages in the group. They will be asked to read the two messages and respond to a series of questions after each of the 9 screenshots.
Intervention Start Date
2025-01-16
Intervention End Date
2025-02-15

Primary Outcomes

Primary Outcomes (end points)
For each image, respondents will be asked 7 questions: (1) How interesting is the message? (2) How likely would you be to forward one of these messages? (3) How likely would you be to reply to one of these messages? (4) How confident are you that the information shared is true? (5) Does this chat change your opinion about the DMK? (6) Does this chat change your opinion about the AIADMK? (7) How entertaining is the chat? These questions will be answered using a Likert scale. We will analyze these outcomes in isolation and jointly using an inverse covariance index following Anderson (2008).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
There are 9 possible combinations of messages:

(1) Party-party (with reply box)
(2) Party-party (no reply box)
(3) Party-individual (individual agrees)
(4) Party-individual (individual neutral)
(5) Party-individual (individual disagrees)
(6) Individual-individual (individual 2 agrees)
(7) Individual-individual (individual 2 neutral)
(8) Individual-individual (individual 2 disagrees)
(9) Individual-individual (both from the same individual)

Comparing 1 vs. 2 estimates the role of "voice" (being able to reply)
Comparing {3, 4, 5} vs. {6, 7, 8} and 1 vs. 9 estimates the role of sender identity (party vs. individual)
Comparing {3, 7} vs. {4, 8} vs. {5, 9} estimates the role of agreement and disagreement
Comparing 7 vs. 9 estimates the role of hearing from multiple people

These are the primary comparisons of interest.

Individuals will be recruited for an online survey using Facebook ads.
Experimental Design Details
Not available
Randomization Method
Randomization occurs within subject: each subject will see all 9 of the possible message combinations described above. The subjects' 9 screenshots will be created by taking a bank of 18 possible messages, and randomly assigning them to a position within the 9 possible combinations described above without replacement.
Randomization Unit
Individual-message
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
We will recruit approximately 3000 individuals. Each individual will see 9 randomized messages, so we will treat these as unique observations, including individual fixed effects and clustering standard errors at the individual level.
Sample size: planned number of observations
27000 person-image pairs (3000 individuals will see 9 screenshots each). This may be lower depending on recruitment ad click rates and survey completion rates (respondents who view some screenshots but do not complete all 9 will be retained in the sample).
Sample size (or number of clusters) by treatment arms
3000 individuals for each of the 9 types of message combinations.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)