Russian Disinformation in Kenya

Last registered on August 27, 2026

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Pre-Trial

Trial Information

General Information

Title

Russian Disinformation in Kenya

RCT ID

AEARCTR-0019435

Initial registration date

August 20, 2026

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

August 27, 2026, 11:45 AM EDT

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

Locations

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Primary Investigator

Name

Maria Berlin

Affiliation

SITE

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Other Primary Investigator(s)

PI Name

Anders Olofsgård

PI Affiliation

Stockholm Institute of Transition Economics

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PI Name

Anastasiia Arbuzova

PI Affiliation

Kiel Institute

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Additional Trial Information

Status

On going

Start date

2026-07-30

End date

2026-09-15

Keywords

Other

Additional Keywords

disinformation, social media

JEL code(s)

Secondary IDs

Prior work

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

Abstract

This study examines how young adults in urban Kenya respond to potentially misleading information on social media and whether short warning messages can help people assess such information. Approximately 5,000 people aged 18–40 in Nairobi and other urban areas of Kenya will participate in an online survey.
Participants will be shown two examples of social media content concerning topics relevant to Kenya and international affairs. They will then see different types of messages designed to alert people to potentially misleading or manipulative information. These warnings vary in who provides the warning, how the source of the potentially misleading information is described, and how the warning is presented, for example as social media content or a radio advertisement. Some participants will not receive a warning, allowing us to compare responses across groups.
The study will examine whether these different approaches affect people's willingness to share social media content, how credible they find the information, and their views on international actors. The broader aim is to better understand how people in Kenya respond to foreign influence and misleading information online, and which types of warnings may help people identify and resist such content.

External Link(s)

Registration Citation

Citation

Arbuzova, Anastasiia, Maria Berlin and Anders Olofsgård. 2026. "Russian Disinformation in Kenya." AEA RCT Registry. August 27. https://doi.org/10.1257/rct.19435-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

The study fields a cross-sectional survey with an embedded experiment among approximately 5,000 individuals aged 18–40 in Nairobi and other urban centres across Kenya. Respondents are asked to read two social media posts, one questioning the motive behind western companies selling gene-modified crops in Kenya, and the second mimicking the language used in posts trying to attract Kenyans to sign up for work in the Russian military. To encourage respondents to read the messages carefully they are asked to rate the posts based on spelling and grammar. Respondents are then randomized into a control group and eight treatment arms receiving variations of disinformation-debunking warnings. Warnings differ across three dimensions: the source of the disinformation warning (European Union vs. a local independent fact-checking organization), whether the spread of disinformation is attributed explicitly to Russia or to a generic foreign power, and the medium of the message (radio ad versus a social media post). The key outcome variable is social media sharing intention, but we also look at perceived message credibility, and opinions on global powers.

Intervention Start Date

2026-07-30

Intervention End Date

2026-08-25

Primary Outcomes

Primary Outcomes (end points)

Social media sharing intention.

Primary Outcomes (explanation)

Social media sharing intention is the binary answer to the question whether the respondent would share the message if they encountered in their social media feed.

Secondary Outcomes

Secondary Outcomes (end points)

Intention to discuss the messages with friends, family and colleagues; opinions towards global powers; suspicion about the message; credibility of the warning.

Secondary Outcomes (explanation)

Intention to discuss the messages with friends, family and colleagues is the binary answer to the question whether respondents would discuss the content of the post with their social circles.
Opinions towards global powers is the five point agreement with each of the following statements "1. China gave Kenya huge loans to build the railway between Mombasa and Nairobi, knowing the country might struggle to repay them, so that China could eventually gain control over Mombasa port and other strategic assets.

2. NATO began the Ukraine war by promising Ukraine membership and placing weapons on Russia's border. Russia had no choice but to defend itself.

3. European countries grew wealthy by colonizing and exploiting Africa for centuries, and the aid and trade deals they offer African countries today are really just a new way to keep control over Africa's resources and economy."
Suspicion about the message is the five point scale answer to the question about how suspicious the respondent found the message. Credibility of the warning is the five point scale answer to the question about how credible the respondent found the warning.

Experimental Design

The study uses a 2×2×2 factorial design, crossing three binary treatment dimensions, plus a control group, yielding nine experimental arms. The three treatment dimensions are:
• Warning source: European Union (EU) vs. local independent fact-checking organization (hereafter 'Local NGO')
• Actor attribution: the false message is attributed explicitly to Russia vs. attributed to a generic unspecified foreign power
• Warning medium: the warning is delivered as a social media post or a radio add.

Experimental Design Details

Not available

Randomization Method

Randomization is implemented at the survey programming level, with 1,000 respondents assigned to the control group and 500 with equal probability to one of the eight treatment groups. Assignment to each group is determined before the respondent answers any questions. Randomization is stratified by age group, education, admin1 region, and gender to ensure balance on these dimensions across arms. Treatment assignment is recorded automatically by the survey platform.

Randomization Unit

Individual.

Was the treatment clustered?