Authors

Discussion

In this paper we present a case study to illustrate a new model for studying disinformation. Focused on (though not restricted to) the Russian context, the model is designed to take account of (a) terminological issues relating to historico-cultural context (e.g. the classification of poor journalistic practice including skewed sensationalised headlines as disinformation); (b) the shift of attention away from individual actors affiliated to discrete states to the translingual and transcultural networks in which disinformation is produced, disseminated and consumed; (b) the acquisition and/or loss of disinformation status across temporal, geopolitical and linguacultural boundaries; and (c) the dialogical relationship between (dis)information providers and counter-disinformation services.

After outlining the model, we will turn to our illustrative case study which draws on COVID-related media reports, predefined as disinformation in Europe’s largest database of ‘disinformation narratives’, EUvsDisinfo. The web crawler, Hyphe, is first used to generate a corpus of hyperlinked pages documenting instances of the promotion by outlets traced by EUvsDisinfo to Russia of dubious COVID-19 treatments. The digital research platform IssueCrawler, and its ‘Lippmannian Device’ tool, are then deployed to reveal a network of related websites cited within EUvsDisinfo and, in turn, by further outlets.  The resulting dataset of 181 media stories includes multiplatform English, Russian, Georgian, French, Arabic and Vietnamese output produced by outlets run by multiple actors, including Russian, French. and American. A Critical Discourse Analysis of sample stories reveals (a) changes in the narratives, depending on the timing of the specific claim’s acquisition or loss of disinformation status in dominant public discourses; (b) variation in the ways stories identified as disinformation are framed for different linguacultural audiences; and (c) how these framings show sensitivity to audience-specific notions of credibility. Scrutiny of Facebook audience engagement with selected reports targets significant user profiles and individual posts. We focus on new meanings that claims acquire as they are reappropriated by new social media knowledge networks. Finally, we analyse EUvsDisinfo ‘disinformation disproof’ commentaries, revealing how they prompt Russian counteraccusations which are in turn added to the database, highlighting reciprocity patterns which, we argue, are key to the disinformation life cycle our model seeks to capture.