TL;DR
This study analyzes 14 million tweets from the 2016 US election, revealing that social bots disproportionately amplified low-credibility content, especially early in viral spread, influencing human retweets and misinformation dissemination.
Contribution
It provides systematic, large-scale evidence of social bots' role in spreading low-credibility content during a major political event.
Findings
Social bots are more active in early spreading moments.
Accounts spreading low-credibility content are more likely to be bots.
Bots target influential users and amplify misinformation effectively.
Abstract
The massive spread of digital misinformation has been identified as a major global risk and has been alleged to influence elections and threaten democracies. Communication, cognitive, social, and computer scientists are engaged in efforts to study the complex causes for the viral diffusion of misinformation online and to develop solutions, while search and social media platforms are beginning to deploy countermeasures. With few exceptions, these efforts have been mainly informed by anecdotal evidence rather than systematic data. Here we analyze 14 million messages spreading 400 thousand articles on Twitter during and following the 2016 U.S. presidential campaign and election. We find evidence that social bots played a disproportionate role in amplifying low-credibility content. Accounts that actively spread articles from low-credibility sources are significantly more likely to be bots.…
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