Comparative analysis of social bots and humans during the COVID-19 pandemic

Ho-Chun Herbert Chang () and Emilio Ferrara ()
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Ho-Chun Herbert Chang: University of Southern California
Emilio Ferrara: Information Science Institute

Journal of Computational Social Science, 2022, vol. 5, issue 2, No 11, 1409-1425

Abstract: Abstract Using more than 4 billion tweets and labels on more than 5 million users, this paper compares the behavior of humans and bots politically and semantically during the pandemic. Results reveal liberal bots are more central than humans in general, but less important than institutional humans as the elite circle grows smaller. Conservative bots are surprisingly absent when compared to prior work on political discourse, but are better than liberal bots at eliciting replies from humans, which suggest they may be perceived as human more frequently. In terms of topic and framing, conservative humans and bots disproportionately tweet about the Bill Gates and bio-weapons conspiracy, whereas the 5G conspiracy is bipartisan. Conservative humans selectively ignore mask-wearing and we observe prevalent out-group tweeting when discussing policy. We discuss and contrast how humans appear more centralized in health-related discourse as compared to political events, which suggests the importance of credibility and authenticity for public health in online information diffusion.

Keywords: Social bots; Twitter; Covid-19; Political asymmetry (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s42001-022-00173-9

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