Department of Computer Science and Network Science and Technology Center, Rensselaer Polytechnic Institute, Troy, NY, USA.
University of Brescia, Brescia, Italy.
Nat Hum Behav. 2023 Jun;7(6):904-916. doi: 10.1038/s41562-023-01550-8. Epub 2023 Mar 13.
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.
社交媒体已经改变了政治传播动态超过十年。在这里,我们使用近十亿条推文,分析了 2016 年和 2020 年美国总统选举期间 Twitter 新闻媒体格局的变化。我们利用政治偏见和事实核查工具,衡量政治偏见内容的数量和传播此类信息的用户数量。然后,我们确定有影响力的用户——在 Twitter 网络中传播新闻能力最大的用户。我们观察到,2016 年至 2020 年间,虚假和极度偏见内容的比例有所下降。然而,结果表明,在用户和影响者层面,两党选举中回声室行为和潜在意识形态两极化现象日益严重。