How do social media feed algorithms affect attitudes and behavior in an election campaign?
Journal
Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511
Informations de publication
Date de publication:
28 07 2023
28 07 2023
Historique:
medline:
31
7
2023
pubmed:
27
7
2023
entrez:
27
7
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 37498999
doi: 10.1126/science.abp9364
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM