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Academic Research

  • Journal Article

    Like-Minded Sources On Facebook Are Prevalent But Not Polarizing

    • Brendan Nyhan, 
    • Jaime Settle, 
    • Emily Thorson, 
    • Magdalena Wojcieszak
    • Pablo Barberá
    • Annie Y. Chen, 
    • Hunt Alcott, 
    • Taylor Brown, 
    • Adriana Crespo-Tenorio, 
    • Drew Dimmery, 
    • Deen Freelon, 
    • Matthew Gentzkow, 
    • Sandra González-Bailón
    • Andrew M. Guess
    • Edward Kennedy, 
    • Young Mie Kim, 
    • David Lazer, 
    • Neil Malhotra, 
    • Devra Moehler, 
    • Jennifer Pan, 
    • Daniel Robert Thomas, 
    • Rebekah Tromble, 
    • Carlos Velasco Rivera, 
    • Arjun Wilkins, 
    • Beixian Xiong, 
    • Chad Kiewiet De Jong, 
    • Annie Franco, 
    • Winter Mason, 
    • Natalie Jomini Stroud, 
    • Joshua A. Tucker

    Nature, 2023

    View Article View abstract

    Many critics raise concerns about the prevalence of ‘echo chambers’ on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from ‘like-minded’ sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

  • Journal Article

    How Do Social Media Feed Algorithms Affect Attitudes and Behavior in an Election Campaign?

    • Andrew M. Guess
    • Neil Malhotra, 
    • Jennifer Pan, 
    • Pablo Barberá
    • Hunt Alcott, 
    • Taylor Brown, 
    • Adriana Crespo-Tenorio, 
    • Drew Dimmery, 
    • Deen Freelon, 
    • Matthew Gentzkow, 
    • Sandra González-Bailón
    • Edward Kennedy, 
    • Young Mie Kim, 
    • David Lazer, 
    • Devra Moehler, 
    • Brendan Nyhan, 
    • Jaime Settle, 
    • Calos Velasco-Rivera, 
    • Daniel Robert Thomas, 
    • Emily Thorson, 
    • Rebekah Tromble, 
    • Beixian Xiong, 
    • Chad Kiewiet De Jong, 
    • Annie Franco, 
    • Winter Mason, 
    • Natalie Jomini Stroud, 
    • Joshua A. Tucker

    Science, 2023

    View Article View abstract

    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.

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