Identifying and characterizing superspreaders of low-credibility content on Twitter

被引:0
|
作者
Deverna, Matthew R. [1 ]
Aiyappa, Rachith [1 ]
Pacheco, Diogo [1 ,2 ]
Bryden, John [1 ]
Menczer, Filippo [1 ,3 ]
Guarino, Stefano
Guarino, Stefano
Guarino, Stefano
机构
[1] Indiana Univ, Observ Social Media, Bloomington, IN 47405 USA
[2] Univ Exeter, Dept Comp Sci, Exeter, England
[3] Luddy Ctr Artificial Intelligence, Bloomington, IN USA
来源
PLOS ONE | 2024年 / 19卷 / 05期
基金
美国国家科学基金会;
关键词
D O I
10.1371/journal.pone.0302201
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportionate amount of low-credibility content-so-called superspreaders-are at the center of this problem. We quantitatively confirm this hypothesis and introduce simple metrics to predict the top superspreaders several months into the future. We then conduct a qualitative review to characterize the most prolific superspreaders and analyze their sharing behaviors. Superspreaders include pundits with large followings, low-credibility media outlets, personal accounts affiliated with those media outlets, and a range of influencers. They are primarily political in nature and use more toxic language than the typical user sharing misinformation. We also find concerning evidence that suggests Twitter may be overlooking prominent superspreaders. We hope this work will further public understanding of bad actors and promote steps to mitigate their negative impacts on healthy digital discourse.
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页数:17
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