The growing dissension towards the political handling of COVID-19, widespread job losses, backlash to extended lockdowns, and hesitancy surrounding the vaccine are propagating toxic far-right discourses in the UK. Moreover, the public is increasingly reliant on different social media platforms, including a growing number of participants on the far-right’s fringe online networks, for all pandemic-related news and interactions. Therefore, with the proliferation of harmful far-right narratives and the public’s reliance on these platforms for socialising, the pandemic environment is a breeding ground for radical ideologically-based mobilisation and social fragmentation. However, there remains a gap in understanding how these far-right online communities, during the pandemic, utilise societal insecurities to attract candidates, maintain viewership, and form a collective on social media platforms. The article aims to better understand online far-right mobilisation by examining, via a mixed-methodology qualitative content analysis and netnography, UK-centric content, narratives, and key political figures on the fringe platform, Gab. Through the dual-qualitative coding and analyses of 925 trending posts, the research outlines the platform’s hate-filled media and the toxic nature of its communications. Moreover, the findings illustrate the far-right’s online discursive dynamics, showcasing the dependence on Michael Hogg’s uncertainty-identity mechanisms in the community’s exploitation of societal insecurity. From these results, I propose a far-right mobilisation model termed Collective Anxiety, which illustrates that toxic communication is the foundation for the community’s maintenance and recruitment. These observations set a precedent for hate-filled discourse on the platform and consequently have widespread policy implications that need addressing.
CITATION STYLE
Collins, J. (2023). Mobilising Extremism in Times of Change: Analysing the UK’s Far-Right Online Content During the Pandemic. European Journal on Criminal Policy and Research, 29(3), 355–377. https://doi.org/10.1007/s10610-023-09547-9
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