意识形态
社会化媒体
政治
极化(电化学)
算法
内容(测量理论)
情感(语言学)
计算机科学
广告
互联网隐私
社会心理学
心理学
政治学
业务
化学
数学
万维网
法学
沟通
数学分析
物理化学
作者
Andrew M. Guess,Neil Malhotra,Jennifer Pan,Pablo Barberá,Hunt Allcott,Taylor Brown,Adriana Crespo-Tenorio,Drew Dimmery,Deen Freelon,Matthew Gentzkow,Sandra González‐Bailón,Edward H. Kennedy,Young Mie Kim,David Lazer,Devra Moehler,Brendan Nyhan,Carlos Velasco Rivera,Jaime E. Settle,Daniel Robert Thomas,Emily Thorson
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2023-07-27
卷期号:381 (6656): 398-404
被引量:185
标识
DOI:10.1126/science.abp9364
摘要
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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