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- W4309650732 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." @default.
- W4309650732 created "2022-11-29" @default.
- W4309650732 creator A5052536455 @default.
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- W4309650732 date "2022-11-21" @default.
- W4309650732 modified "2023-09-30" @default.
- W4309650732 title "Measuring exposure to misinformation from political elites on Twitter" @default.
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- W4309650732 doi "https://doi.org/10.1038/s41467-022-34769-6" @default.
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