Abstract
AbstractCOVID-19 has given rise to a lot of malicious content online, including hate speech, online abuse, and misinformation. British MPs have also received abuse and hate on social media during this time. To understand and contextualise the level of abuse MPs receive, we consider how ministers use social media to communicate about the pandemic, and the citizen engagement that this generates. The focus of the paper is on a large-scale, mixed-methods study of abusive and antagonistic responses to UK politicians on Twitter, during the pandemic from early February to late May 2020. We find that pressing subjects such as financial concerns attract high levels of engagement, but not necessarily abusive dialogue. Rather, criticising authorities appears to attract higher levels of abuse during this period of the pandemic. In addition, communicating about subjects like racism and inequality may result in accusations of virtue signalling or pandering by some users. This work contributes to the wider understanding of abusive language online, in particular that which is directed at public officials.
Funder
ESRC National Centre for Research Methods, University of Southampton
University of Sheffield
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Reference77 articles.
1. Andreouli, E., Kaposi, D., & Stenner, P. (2019). Brexit and emergent politics: In search of a social psychology. Journal of Community & Applied Social Psychology,29(1), 6–17.
2. Ashley, W. (2014). The angry black woman: The impact of pejorative stereotypes on psychotherapy with black women. Social Work in Public Health,29(1), 27–34.
3. Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D. Y., Chen, L., et al. (2020). Presumed asymptomatic carrier transmission of COVID-19. Jama,323(14), 1406–1407.
4. Barbour, R. S. (2001). Checklists for improving rigour in qualitative research: A case of the tail wagging the dog? Bmj,322(7294), 1115–1117.
5. Bhaskaran, J., Kamath, A., & Paul, S. (2020). Detecting insults in social commentary. https://www.kaggle.com/c/detecting-insults-in-social-commentary/data. Accessed 17 Feb 2020.
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