Observatory on Social Media, Indiana University, Bloomington, IN, USA.
Department of Computer Science, University of Exeter, Exeter, UK.
Nat Commun. 2021 Sep 22;12(1):5580. doi: 10.1038/s41467-021-25738-6.
Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.
社交媒体平台试图遏制滥用和错误信息,但却被指责存在政治偏见。我们部署了中立的社交媒体机器人,让它们开始在 Twitter 上关注不同的新闻来源,并对其进行跟踪,以探究平台机制和用户交互产生的不同偏见。我们没有发现新闻推送存在强烈或一致的政治偏见的证据。尽管如此,美国 Twitter 用户所接触到的新闻和信息,在很大程度上取决于他们早期关联账户的政治倾向。保守派账户的互动倾向于右翼,而自由派账户则会接触到温和的内容,从而将他们的体验转移到政治中心。党派账户,尤其是保守派账户,往往会获得更多的关注者,并关注更多的自动化账户。保守派账户也发现自己处于更密集的社区中,并接触到更多低可信度的内容。