How do social media feed algorithms affect attitudes and behavior in an election campaign?
Andrew M GuessNeil MalhotraJennifer PanPablo BarberÁHunt AllcottTaylor BrownAdriana Crespo-TenorioDrew DimmeryDeen FreelonMatthew GentzkowSandra Gonzalez-BailonEdward H KennedyYoung Mie KimDavid M J LazerDevra MoehlerBrendan NyhanCarlos Velasco RiveraJaime SettleDaniel Robert ThomasEmily ThorsonRebekah TrombleArjun WilkinsMagdalena WojcieszakBeixian XiongChad Kiewiet de JongeAnnie FrancoWinter MasonNatalie Jomini StroudJoshua A TuckerPublished in: Science (New York, N.Y.) (2023)
We investigated the effects of Facebook's and Instagram's feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users' on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.