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

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posted on 2025-03-11, 14:54 authored by Suzanne ElayanSuzanne Elayan, Martin SykoraMartin Sykora

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.

History

School

  • Loughborough Business School

Published in

Journal of Computational Social Science

Volume

7

Pages

2481 - 2504

Publisher

Springer Nature

Version

  • VoR (Version of Record)

Rights holder

© Crown

Publisher statement

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acceptance date

2024-07-21

Publication date

2024-08-09

Copyright date

2024

ISSN

2432-2717

eISSN

2432-2717

Language

  • en

Depositor

Dr Martin Sykora. Deposit date: 9 August 2024

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