Fraudulent participation in online surveys in the age of AI: a case-based warning for researchers

Online surveys and remote recruitment have become central to contemporary human-subject research because they broaden reach, lower costs, and enable more flexible participation. However, these advantages also introduce new risks to participant authenticity and data integrity. Here, we draw on a multi-phase study of how remote work arrangements affect employees’ work and personal life to highlight an emerging methodological challenge: fraudulent participants may enter online research pipelines with responses that appear plausible and internally consistent, making them difficult to detect from survey data alone. In our case, suspicious entries became visible only through later workflow stages, when device-based GPS data and identity-related checks linked to incentive delivery revealed inconsistencies with the study’s geographic eligibility criteria. We argue that participant authenticity in online research should be treated as an active methodological concern and outline practical, layered safeguards to help protect study integrity in increasingly digital and potentially AI-assisted research settings.

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Publication Details

Journal
International Journal of Social Research Methodology
Published
2026-08-28
DOI
https://doi.org/10.1080/13645579.2026.2726836
Primary Topic
Survey Methodology and Nonresponse
Type
article
Field-Weighted Citation Impact
0.00

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article

Fraudulent participation in online surveys in the age of AI: a case-based warning for researchers

Olle Järv, Riku Reunamäki, Milad S. Malekzadeh
International Journal of Social Research Methodology
Survey Methodology and Nonresponse
article

Fraudulent participation in online surveys in the age of AI: a case-based warning for researchers

Olle Järv, Riku Reunamäki, Milad S. Malekzadeh
article en

Abstract

Online surveys and remote recruitment have become central to contemporary human-subject research because they broaden reach, lower costs, and enable more flexible participation. However, these advantages also introduce new risks to participant authenticity and data integrity. Here, we draw on a multi-phase study of how remote work arrangements affect employees’ work and personal life to highlight an emerging methodological challenge: fraudulent participants may enter online research pipelines with responses that appear plausible and internally consistent, making them difficult to detect from survey data alone. In our case, suspicious entries became visible only through later workflow stages, when device-based GPS data and identity-related checks linked to incentive delivery revealed inconsistencies with the study’s geographic eligibility criteria. We argue that participant authenticity in online research should be treated as an active methodological concern and outline practical, layered safeguards to help protect study integrity in increasingly digital and potentially AI-assisted research settings.

International Journal of Social Research Methodology
University of Helsinki (FI), Tampere University (FI), University of Tartu (EE)
European Commission, Tartu Ülikool, HORIZON EUROPE Framework Programme, Research Executive Agency
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Survey Methodology and Nonresponse
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