Journal of Online Trust and Safety · 2022 · 14 citations · 29 references
Public AffairsCommunicationPolitical CommunicationAmerican PoliticsPublic OpinionRecommender SystemsDisinformationElection FraudMisinformation DetectionOnline CampaigningSource CredibilityElection LegitimacyMisinformation In CampaignsMisinformation In ElectionsMisinformation In Online CommunitiesOnline Social InteractionPerceptionRecommendation System EffectsSocial Influence Online
Skepticism about the outcome of the 2020 presidential election in the United States led to a historic attack on the Capitol on January 6th, 2021 and represents one of the greatest challenges to America's democratic institutions in over a century. Narratives of fraud and conspiracy theories proliferated over the fall of 2020, finding fertile ground across online social networks, although little is know about the extent and drivers of this spread. In this article, we show that users who were more skeptical of the election's legitimacy were more likely to be recommended content that featured narratives about the legitimacy of the election. Our findings underscore the tension between an "effective" recommendation system that provides users with the content they want, and a dangerous mechanism by which misinformation, disinformation, and conspiracies can find their way to those most likely to believe them.
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A Simple Sequentially Rejective Multiple Test Procedure
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Deep Neural Networks for YouTube Recommendations
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