Understanding the emotional response to COVID-19 information in news and social media: A mental health perspective

Jones, Rosalind and Mougouei, Davoud ORCID: https://orcid.org/0000-0002-4271-9174 and Evans, Simon L. (2021) Understanding the emotional response to COVID-19 information in news and social media: A mental health perspective. Human Behavior and Emerging Technologies, 3 (5). pp. 832-842.


Abstract

The impact of the COVID-19 pandemic and ensuing social restrictions has been profound, affecting the health, livelihoods, and wellbeing of populations worldwide. Studies have shown widespread effects on mental health, with an increase in stress, loneliness, and depression symptoms related to the pandemic. Media plays a critical role in containing and managing crises, by informing society and fostering positive behavior change. Social restrictions have led to a large increase in reliance on online media channels, and this can influence mental health and wellbeing. Anxiety levels, for instance, may be exacerbated by exposure to COVID-related content, contagion of negative sentiment among social networks, and “fake news.” In some cases, this may trigger abstinence, leading to isolation and limited access to vital information. To be able to communicate distressing news during crises while protecting the wellbeing of individuals is not trivial; it requires a deeper understanding of people's emotional response to online and social media content. This paper selectively reviews research into consequences of social media usage and online news consumption for wellbeing and mental health, focusing on and discussing their effects in the context of the pandemic. Advances in Artificial Intelligence and Data Science, for example, Natural Language Processing, Sentiment Analysis, and Emotion Recognition, are discussed as useful methods for investigating effects on population mental health as the pandemic situation evolves. We present suggestions for future research, and for using these advances to assess large data sets of users' online content, to potentially inform strategies that enhance the mental health of social media users going forward.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 - 31 Dec 2021)
Date Deposited: 14 Feb 2022 03:40
Last Modified: 05 Aug 2022 03:10
Uncontrolled Keywords: artificial intelligence; coronavirus; COVID-19; data science; emotions; mental health; natural language processing; news; pandemic; social media
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified
Identification Number or DOI: https://doi.org/10.1002/hbe2.304
URI: http://eprints.usq.edu.au/id/eprint/46103

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