Dynamics of COVID-19 blame attribution: A corpus-based analysis of readers’ comments in response to UK online news

Abstract

This study adopts a longitudinal approach to analyse the attribution of blame in online comments for the emergence, continuation and consequences of COVID-19. It uses an innovative approach to distil a specialised corpus of readers’ comments in response to UK online news articles about COVID-19, before applying corpus linguistic techniques to identify the principal actors attributed as blame agents. The research found that both internal (the government and the prime minister) and external actors (China and the World Health Organization) were identified as blame agents in comments. The analysis also indicates the presence of blame attribution towards people, their own actions and behaviours, which, in part, may be a consequence of government and public health messaging that emphasised individual responsibility to reduce transmission of the virus. This is distinctive, with significance for public understanding of COVID-19 and for future pandemic communication planning.