Measuring exposure to misinformation from political elites on Twitter

Abstract

Misinformation can come directly from public figures and organizations (referred to here as “elites”). Here, we develop a tool for measuring Twitter users’ exposure to misinformation from elites based on the public figures and organizations they choose to follow. Using a database of professional fact-checks by PolitiFact, we calculate falsity scores for 816 elites based on the veracity of their statements. We then assign users an elite misinformation-exposure score based on the falsity scores of the elites they follow on Twitter. Users’ misinformation-exposure scores are negatively correlated with the quality of news they share themselves, and positively correlated with estimated conservative ideology. Additionally, we analyze the co-follower, co-share, and co-retweet networks of 5000 Twitter users and find an ideological asymmetry: estimated ideological extremity is associated with more misinformation exposure for users estimated to be conservative but not for users estimated to be liberal. Finally, we create an open-source R library and an Application Programming Interface (API) making our elite misinformation-exposure estimation tool openly available to the community.

Accuracy and social motivations shape judgements of (mis)information

“…Several studies have also found that US conservatives or Republicans tend to believe in and share more misinformation than US liberals or Democrats [26][27][28][29][30][31][32] . One interpretation behind this asymmetry is that US conservatives are exposed to more low-quality information and thus have less accurate political knowledge, perhaps due to US conservative politicians and news media sources sharing less accurate information 33,34 . Another interpretation again focuses on motivation, suggesting that US conservatives may, in some contexts, have greater motivations to believe ideologically or identity-consistent claims that could interfere with their motivation to be accurate 31,[35][36][37] .…”

Partisan conflict over content moderation is more than disagreement about facts

“…For example, Republicans might have developed lower baseline moderation preferences because they think that the content moderation system disproportionately targets them. Alternatively, if Republicans' threshold for unfollowing users mimics their high threshold for removing content, then our findings could also explain why conservatives are exposed to more misinformation in general (58)(59)(60)(61)(62). Future research could explore this in more detail.…”

Donate to help us fight back: Political fundraising and toxic rhetoric online

“…Although originally intended to identify toxicity in online comments, the API's utility stretches beyond it, and scholars have begun to employ this tool in their analyses of online text. For example, in an analysis of misinformation circulated by political elites on Twitter, Mosleh and Rand (2022) theorize that social media users subjected to more misinformation will use more toxic rhetoric and expressions of moral outrage in their tweets. They used the Perspective API to measure the toxicity of advertisements and showed that Twitter users who followed elites who posted more false information were inclined to use more toxic language in their posts.…”