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COVID-19 and Figures of Blame: Discursive Representations of Blame for COVID-19 and its Impacts in UK Online News.

Matthews, J. and Heesambee, F., 2023. COVID-19 and Figures of Blame: Discursive Representations of Blame for COVID-19 and its Impacts in UK Online News. Discourse and Communication. (In Press)

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DOI: 10.1177/17504813231219458

Abstract

As publics have attempted to make sense of the COVID-19 crisis and its longer-term impacts there has been an inevitable search for blame. Emergent research on the attribution of blame has focused exclusively on the initial outbreak, with insufficient attention paid to how countries have responded to the pandemic. Our study adopts a longitudinal approach, examining the figures of blame that emerged across the UK’s experience of COVID-19, including subsequent waves of COVID-19. By sampling articles from three online UK news outlets (BBC; The Guardian; Mail Online), we analyse the linguistic elements and discourse strategies that contribute to the representation of specific actors as figures of blame in news coverage of COVID-19. To identify actors and their representations we focus on three elements: 1) direct, indirect or implied reference to an actor; 2) an expression of anger, resentment, or frustration towards this actor, 3) textual and discursive features that nominate agency for their actions or inaction for a negative outcome. Our analysis shows that three prominent figures of blame emerged across the period of analysis. The primary actor represented as a figure of blame was the UK government. This, we argue, differs from the initial phases of the outbreak where there was an emphasis on externalising blame. We also found, however, that the public and the individual were constructed as figures of blame. For the latter it was through an emphasis on personal responsibility in the adoption of preventative behaviours and in following COVID-19 restrictions. We conclude the paper by exploring the significance of these findings for the communicative dynamics of the pandemic.

Item Type:Article
ISSN:1750-4813
Uncontrolled Keywords:blame; COVID-19; online news; discourse analysis; social actor analysis
Group:Faculty of Media & Communication
ID Code:39419
Deposited By: Symplectic RT2
Deposited On:25 Jan 2024 11:02
Last Modified:20 Feb 2024 11:48

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