Mistranslating Deceit: Citizen Engagement with Disinformation in Poland, Romania, Serbia and Arabic-speaking Communities in the UK, 2025

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 forms part of the audience research strand of the AHRC-funded project (Mis)Translating Deceit: Citizen Engagement with Disinformation in Poland, Romania, Serbia and Arabic-speaking Communities in the UK. It comprises qualitative data collected through online focus groups conducted in four socio-linguistic settings: Poland, Romania, Serbia, and Arabic-speaking communities in the United Kingdom. The data capture how citizens in different cultural and linguistic contexts perceive disinformation as a social problem and how they interpret and engage with concrete examples labelled as disinformation by local fact-checking organisations. The dataset includes English-language transcripts of all focus groups, alongside supporting research materials such as participant information sheets, consent forms, the focus group protocol, a description of the disinformation examples used, and the coding schedule. Focus groups were stratified by generation and addressed media use, perceptions of misleading information, trust in news sources, and audience responses to disinformation related to the Russia–Ukraine war and LGBTQ+ rights. All data were collected, anonymised and processed in line with institutional ethical standards for research involving human participants.

The Ukraine war, Covid-19 and the Trump presidency highlight the threat disinformation poses to democracy. Yet the implicit persistence of Cold War binaries - pitting democratic 'truth-telling' against totalitarian 'deceit', even in relation to homegrown disinformation - has seriously hampered attempts to counter this problem in the multipolar, Big Data age. The result is a glut of poorly differentiated terms: disinformation, misinformation, fake news, post-truth, and astroturfing, to name just a few. This dichotomous viewpoint heeds neither the contested meaning of disinformation, nor how the narratives it designates change across time, languages and cultures. These limitations explain the emergence of a 'Big Disinfo' industry: the burgeoning of monitoring initiatives whose success depends on maintaining the sense of an undifferentiated morass of toxicity rather than trying to draw out fine distinctions of language, meaning, culture or context. In conflating disinformation with related concepts like propaganda, conspiracy theories, and trolling, such reductionism obscures the operational modes of disinformation actors, furnishing them with counter-narratives that use the very lexicon deployed against them. By reconstructing disinformation's multiple border crossings - temporal, linguistic, cultural - (Mis)translating Deceit (MD) will radically re-orient existing approaches to disinformation. It will interrogate common misconceptions about disinformation, treating it as a translingual, historically mutating phenomenon forged within the socio-politically contingent realm of discourse. Big Disinfo's abiding focus on Kremlin malfeasance, bolstered by the Ukraine war, motivates our emphasis on multilingual narratives linked to Russia and the USSR. But by pinpointing the Russian node in a vast translingual network, we will create a model for identifying and combatting disinformation practices of diverse provenance. With impact at its core, MD proposes a potent interdisciplinary intervention, showcasing how humanities scholars can address major global challenges. Forging a novel, cross-sectoral collaborative model involving leading academics, the UK's top think tank, Chatham House, a European disinformation monitor (EUDisinfoLab) and OFCOM, it draws on expertise in history, translation studies, audience research, media studies and security policy. Outputs include a book, seminar series and journal articles pitched to media and reception studies, language-based area studies, history, translation studies and medical humanities. Our Chatham House-led impact programme will generate reports for stakeholders, including the FCO and DCMS, and a user-oriented version of our toolset.