Hate Speech and Covid-19 Risk Communication: A Critical Corpus-based Analysis of Risk and Xenophobia in Twitter

The article investigates the role of affect and racial discrimination in the appraisal of risk communication related to covid-19 in Twitter. Building on the premises that epidemics are not just an incidental but a predictable trigger of fear, hate and mistrust and or/solidarity, the study will investigate epidemics as possible sites of intolerance and/or encounter, connectivity and conviviality. During the last decade, social media have intensified their role as a channel for the communication of scientific evaluation of risk. Scientific experts adopt non-persuasive communication, trusting data to speak for themselves, and describe both benefits and risks, often in quantitative terms. Yet they are cautious and generally speak about probabilities, which do not translate well in social media which “rarely present bald facts or narrate activities and events without adopting some kind of evaluative stance […] sharing and contesting opinion and sentiment is central to social media discourse.” (Zappavigna 2017). The remediation of risk communication in social media entails the resort to affect for persuasion purposes related to the enactment of social identities and affiliations (Martin and White 2005). In order to communicate covid-19 related risks, online news media coverage of the outbreak often resorted to feelings related to eco-social insecurity such as fear and anxiety. However, such fear appeals arguably engendered the promotion of a set of common values which resulted in hate speech directed at the affected populations. Hence, this study will investigate whether hate speech emerged during the pandemic in correlation to fear appeals in risk communication discourse. More specifically, whether such appeals fuelled the re-irruption of nationalist and xenophobic discourses during the outbreak. It will do so by associating the findings on affect with findings on the “sociosemantic inventory” related to the representation of social actors and discrimination (nomination strategies, predicational strategies, argumentation strategies, perspectivation, framing, intensifying and mitigation strategies etc.) (Van Leeuwen 1996; Reisigl and Wodak 2001). Based on these premises, the article will provide an analysis of the remediation of covid-19 risk communication discourse in a specialized twitter corpus. The data will be analysed according to an approach which draws upon findings in Critical Social Media Discourse Analysis, Appraisal Linguistics, and Corpus Linguistics. Corpus Linguistics methodological tools such as quantitative techniques will be combined with the analysis of context and discourse structural evaluation through qualitative assessments (Baker 2006; Martin and White 2005; Thomson and White 2008; Zappavigna 2012). Therefore, the search will be narrowed from bulk data retrieval to identify the lexical and grammatical resources used to express attitude oriented to affect. The project aims to draw some conclusions on how transnational/local news media channel information on epidemics and increase/decrease fear, hate and distrust and or solidarity. It hopes that research may spread awareness on the development of ethical protocols for risk communication in the management of epidemics which may result in lower economic and social costs for affected areas.