Digital intermediaries in pandemic times: social media and the role of bots in communicating emotions and stress about Coronavirus

Suzanne Elayan () and Martin Sykora ()
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Suzanne Elayan: Loughborough University
Martin Sykora: Loughborough University

Journal of Computational Social Science, 2024, vol. 7, issue 3, No 9, 2504 pages

Abstract: Abstract COVID-19 impacted citizens around the globe physically, economically, socially, or emotionally. In the first 2 years of its emergence, the virus dominated media in offline and online conversations. While fear was a justifiable emotion; were online discussions deliberately fuelling it? Concerns over the prominent negativity and mis/disinformation on social media grew, as people relied on social media more than ever before. This study examines expressions of stress and emotions used by bots on what was formerly known as Twitter. We collected 5.6 million tweets using the term “Coronavirus” over two months in the early stages of the pandemic. Out of 77,432 active users, we found that over 15% were bots while 48% of highly active accounts displayed bot-like behaviour. We provide evidence of how bots and humans used language relating to stress, fear and sadness; observing substantially higher prevalence of stress and fear messages being re-tweeted by bots over human accounts. We postulate, social media is an emotion-driven attention information market that is open to “automated” manipulation, where attention and engagement are its primary currency. This observation has practical implications, especially online discussions with heightened emotions like stress and fear may be amplified by bots, influencing public perception and sentiment.

Keywords: COVID-19; Coronavirus; Sentiment analysis; Automated social media bots; Stress; Emotions; Attention information market; Social media; Big data (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42001-024-00314-2

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