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Using Social Media to Guard the Ballots: Evidence From a Facebook Campaign To Monitor Elections
Last registered on September 06, 2019

Pre-Trial

Trial Information
General Information
Title
Using Social Media to Guard the Ballots: Evidence From a Facebook Campaign To Monitor Elections
RCT ID
AEARCTR-0004678
Initial registration date
September 05, 2019
Last updated
September 06, 2019 1:47 PM EDT
Location(s)

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Primary Investigator
Affiliation
MIT
Other Primary Investigator(s)
PI Affiliation
U.C. Berkeley
Additional Trial Information
Status
In development
Start date
2019-09-02
End date
2019-12-31
Secondary IDs
Abstract
In this project we plan to use a field experiment that exposes citizens to a large-scale Facebook advertisement campaign encouraging them to report electoral misdeeds around the 2019 Colombian elections. Our experimental design will allow us to study four separate questions: (1) whether their exists a demand for online reporting tools; (2) whether candidates reduce their electoral misdeeds when informed about these types of campaigns; (3) if candidates engage in \textit{signal jamming} of the reporting website strategically; (4) if this type of campaigns induce secondary effects on citizens' voting decisions by increasing the salience of electoral misdeeds.
External Link(s)
Registration Citation
Citation
Garbiras-Diaz, Natalia and Juan Mateo Montenegro Zarama. 2019. "Using Social Media to Guard the Ballots: Evidence From a Facebook Campaign To Monitor Elections." AEA RCT Registry. September 06. https://doi.org/10.1257/rct.4678-1.0.
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Experimental Details
Interventions
Intervention(s)
We randomize approximately 700 Colombian municipalities into two conditions:

T0 - Placebo control group: Municipalities in this group receive a Facebook ad containing a placebo message, reminding people about the 2019 local elections.
T1 - Ad treatment group: Municipalities in this group receive a Facebook ad containing a message encouraging them to report electoral misdeeds through a link sending them to a reporting website, along with the placebo message.

The ad campaigns will last for a week and are aimed to reach at least half of the Facebook users in the municipalities in the sample.

We then cross-randomized the municipalities receiving the ads into three conditions:

- TA. Politician awareness treatment without signal jamming: All of the candidates running for Mayor and their campaign staff in the municipalities in this group will be informed about the monitoring campaign, but they will not be informed about the particular reporting website advertised in the campaign.
- TB. Politician awareness treatment allowing for signal jamming: All of the candidates running for Mayor and their campaign staff in the municipalities in this group will be informed about the monitoring campaign, including the particular reporting website advertised in the campaign.
- TC. No Politician awareness: None of the candidates running for Mayor and their campaign staff in the municipalities in this group will not be informed about the monitoring campaign in any way.
Intervention Start Date
2019-09-02
Intervention End Date
2019-11-15
Primary Outcomes
Primary Outcomes (end points)
- Reports about electoral misdeeds filed from each municipality
- Occurrence of different types of electoral misdeeds measured through survey responses
- Electoral outcomes such as turnout, and vote shares
Primary Outcomes (explanation)
The most common historical types of electoral misdeeds will be measured and also which candidate was engaged in these misdeeds.
Secondary Outcomes
Secondary Outcomes (end points)
- Campaigning activities of candidates
- Trust in different types of institutions
- Interpersonal trust
- Protest and collective action in municipalities
- Interpersonal trust
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
See the above section describing the intervention.
Experimental Design Details
Not available
Randomization Method
Stratified randomization within bins defined by percentiles of the main outcomes. Randomization is done using statistical software
Randomization Unit
Municipalities
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
698
Sample size: planned number of observations
40000
Sample size (or number of clusters) by treatment arms
225 control, 473 in T1, 157 in TA, 155 in TB, 161 in TC.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effects are 0.25 standard deviations for reports and a pooled variable of electoral misdeeds and 0.28 standard deviations for voter turnout.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
MIT's Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
2019-05-16
IRB Approval Number
1904805455