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How do social media feed algorithms affect attitudes and behavior in an election campaign?
Guess, Andrew M; Malhotra, Neil; Pan, Jennifer; Barberá, Pablo; Allcott, Hunt; Brown, Taylor; Crespo-Tenorio, Adriana; Dimmery, Drew; Freelon, Deen; Gentzkow, Matthew; González-Bailón, Sandra; Kennedy, Edward; Kim, Young Mie; Lazer, David; Moehler, Devra; Nyhan, Brendan; Rivera, Carlos Velasco; Settle, Jaime; Thomas, Daniel Robert; Thorson, Emily; Tromble, Rebekah; Wilkins, Arjun; Wojcieszak, Magdalena; Xiong, Beixian; de Jonge, Chad Kiewiet; Franco, Annie; Mason, Winter; Stroud, Natalie Jomini; Tucker, Joshua A.
Afiliação
  • Guess AM; Department of Politics and School of Public and International Affairs, Princeton University, Princeton, NJ, USA.
  • Malhotra N; Graduate School of Business, Stanford University, Stanford, CA, USA.
  • Pan J; Department of Communication, Stanford University, Stanford, CA, USA.
  • Barberá P; Meta, Menlo Park, CA, USA.
  • Allcott H; Stanford Doerr School of Sustainability, Stanford University, Stanford, CA, USA.
  • Brown T; Meta, Menlo Park, CA, USA.
  • Crespo-Tenorio A; Meta, Menlo Park, CA, USA.
  • Dimmery D; Meta, Menlo Park, CA, USA.
  • Freelon D; Research Network Data Science, University of Vienna, Vienna, Austria.
  • Gentzkow M; UNC Hussman School of Journalism and Media, University of North Carolina at Chapel Hill, Chapel, NC, USA.
  • González-Bailón S; Department of Economics, Stanford University, Stanford, CA, USA.
  • Kennedy E; Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA.
  • Kim YM; Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA.
  • Lazer D; School of Journalism and Mass Communication, University of Wisconsin-Madison, Madison, WI, USA.
  • Moehler D; Network Science Institute, Northeastern University, Boston, MA, USA.
  • Nyhan B; Meta, Menlo Park, CA, USA.
  • Rivera CV; Department of Government, Dartmouth College, Hanover, NH, USA.
  • Settle J; Meta, Menlo Park, CA, USA.
  • Thomas DR; Department of Government, William & Mary, Williamsburg, VA, USA.
  • Thorson E; Meta, Menlo Park, CA, USA.
  • Tromble R; Department of Political Science, Syracuse University, Syracuse, NY, USA.
  • Wilkins A; School of Media and Public Affairs and Institute for Data, Democracy, and Politics, The George Washington University, Washington, DC, USA.
  • Wojcieszak M; Meta, Menlo Park, CA, USA.
  • Xiong B; Department of Communication, University of California, Davis, Davis, CA, USA.
  • de Jonge CK; Amsterdam School of Communication Research, University of Amsterdam, Amsterdam, Netherlands.
  • Franco A; Meta, Menlo Park, CA, USA.
  • Mason W; Meta, Menlo Park, CA, USA.
  • Stroud NJ; Meta, Menlo Park, CA, USA.
  • Tucker JA; Meta, Menlo Park, CA, USA.
Science ; 381(6656): 398-404, 2023 07 28.
Article em En | MEDLINE | ID: mdl-37498999
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais Limite: Humans Idioma: En Revista: Science Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mídias Sociais Limite: Humans Idioma: En Revista: Science Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos