Abstract
AbstractSocial 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.
Funder
National Science Foundation
United States Department of Defense | Defense Advanced Research Projects Agency
Beijing Municipal Commission of Education
U.S. Department of Health & Human Services | National Institutes of Health
Publisher
Springer Science and Business Media LLC
Subject
Behavioral Neuroscience,Experimental and Cognitive Psychology,Social Psychology
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