Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections

被引:0
|
作者
James Flamino
Alessandro Galeazzi
Stuart Feldman
Michael W. Macy
Brendan Cross
Zhenkun Zhou
Matteo Serafino
Alexandre Bovet
Hernán A. Makse
Boleslaw K. Szymanski
机构
[1] Rensselaer Polytechnic Institute,Department of Computer Science and Network Science and Technology Center
[2] University of Brescia,Departments of Information Science and Sociology
[3] Ca’ Foscari University of Venice,School of Statistics
[4] Schmidt Futures,Department of Mathematics and Digital Society Initiative
[5] Cornell University,undefined
[6] Capital University of Economics and Business,undefined
[7] Levich Institute and Physics Department,undefined
[8] City College of New York,undefined
[9] University of Zurich,undefined
来源
Nature Human Behaviour | 2023年 / 7卷
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摘要
Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter’s news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume of politically biased content and the number of users propagating such information. We then identify influencers—users with the greatest ability to spread news in the Twitter network. We observe that the fraction of fake and extremely biased content declined between 2016 and 2020. However, results show increasing echo chamber behaviours and latent ideological polarization across the two elections at the user and influencer levels.
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页码:904 / 916
页数:12
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