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A Thematic analysis of highly retweeted early COVID-19 tweets: Consensus, information, dissent, and lockdown life
Thelwall, Michael Thelwall, Saheeda
Thelwall, Michael
Thelwall, Saheeda
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2020-10-23
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Abstract
Purpose: Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings: The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications: Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers, and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications: Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value: This is the first qualitative analysis of general COVID-19-related retweeting.
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Thelwall, M. and Thelwall, S. (2020) A Thematic analysis of highly retweeted early COVID-19 tweets: Consensus, information, dissent, and lockdown life, Aslib Journal of Information Management, 72(6), pp. 945-962. https://doi.org/10.1108/AJIM-05-2020-0134
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Journal article
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en
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This is an accepted manuscript of an article published by Emerald in Aslib Journal of Information Management on 23/10/2020.
The accepted version of the publication may differ from the final published version.
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2050-3806