Algorithmic amplification of politics on Twitter
The role of social media in political discourse has been the topic of intense scholarly and public debate. Politicians and commentators from all sides allege that Twitter’s algorithms amplify their opponents’ voices, or silence theirs. Policy makers and researchers have thus called for increased transparency on how algorithms influence exposure to political content on the platform. Based on a massive-scale experiment involving millions of Twitter users, a fine-grained analysis of political parties in seven countries, and 6.2 million news articles shared in the United States, this study carries out the most comprehensive audit of an algorithmic recommender system and its effects on political content. Results unveil that the political right enjoys higher amplification compared to the political left. Aggregated study data are available upon request from the corresponding authors following the protocol outlined in [ SI Appendix, section 3 ][1]. [1]: https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2025334119/-/DCSupplemental
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