Emotion Bubbles: Emotional Composition of Online Discourse Before and After the COVID-19 Outbreak

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The COVID-19 pandemic has been the single most important global agenda in the past two years. In addition to its health and economic impacts, it has affected people's psychological states, including a rise in depression and domestic violence. We traced how the overall emotional states of individual Twitter users changed before and after the pandemic. Our data, including more than 9 million tweets posted by 9,493 users, suggest that the threat posed by the virus did not upset the emotional equilibrium of social media. In early 2020, COVID-related tweets skyrocketed in number and were filled with negative emotions; however, this emotional outburst was short-lived. We found that users who had expressed positive emotions in the pre-COVID period remained positive after the initial outbreak, while the opposite was true for those who regularly expressed negative emotions. Individuals achieved such emotional consistency by selectively focusing on emotion-reinforcing topics. The implications are discussed in light of an emotionally motivated confirmation bias, which we conceptualize as emotion bubbles that demonstrate the public's resilience to a global health risk.
Publisher
Association for Computing Machinery, Inc
Issue Date
2022-04-25
Language
English
Citation

31st ACM World Wide Web Conference, WWW 2022, pp.2603 - 2613

DOI
10.1145/3485447.3512132
URI
http://hdl.handle.net/10203/298139
Appears in Collection
RIMS Conference PapersCS-Conference Papers(학술회의논문)
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