Identifying how COVID-19-related misinformation reacts to the announcement of the UK national lockdown: An interrupted time-series study



Green, Mark, Musi, Elena ORCID: 0000-0003-2431-455X, Rowe, Francisco ORCID: 0000-0003-4137-0246, Charles, Darren, Pollock, Frances Darlington ORCID: 0000-0001-5544-4459, Kypridemos, Chris ORCID: 0000-0002-0746-9229, Morse, Andrew ORCID: 0000-0002-0413-2065, Rossini, Patricia, Tulloch, John ORCID: 0000-0003-2150-0090, Davies, Andrew ORCID: 0000-0002-3164-9609
et al (show 5 more authors) (2021) Identifying how COVID-19-related misinformation reacts to the announcement of the UK national lockdown: An interrupted time-series study. Big Data & Society, 8 (1). 205395172110138 - 205395172110138.

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Abstract

<jats:p> COVID-19 is unique in that it is the first global pandemic occurring amidst a crowded information environment that has facilitated the proliferation of misinformation on social media. Dangerous misleading narratives have the potential to disrupt ‘official’ information sharing at major government announcements. Using an interrupted time-series design, we test the impact of the announcement of the first UK lockdown (8–8.30 p.m. 23 March 2020) on short-term trends of misinformation on Twitter. We utilise a novel dataset of all COVID-19-related social media posts on Twitter from the UK 48 hours before and 48 hours after the announcement (n = 2,531,888). We find that while the number of tweets increased immediately post announcement, there was no evidence of an increase in misinformation-related tweets. We found an increase in COVID-19-related bot activity post-announcement. Topic modelling of misinformation tweets revealed four distinct clusters: ‘government and policy’, ‘symptoms’, ‘pushing back against misinformation’ and ‘cures and treatments’. </jats:p>

Item Type: Article
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences
Faculty of Health and Life Sciences > Institute of Population Health
Faculty of Humanities and Social Sciences > School of Histories, Languages and Cultures
Faculty of Humanities and Social Sciences > School of the Arts
Faculty of Science and Engineering > School of Environmental Sciences
Depositing User: Symplectic Admin
Date Deposited: 26 Mar 2021 10:28
Last Modified: 02 Dec 2021 08:36
DOI: 10.1177/20539517211013869
URI: https://livrepository.liverpool.ac.uk/id/eprint/3118172