Is stance in fake news expressed differently across languages?

In this corpus study, we examine the use and distribution of stance expressions in fake news in three languages: English, Norwegian and Russian. Stance is a major communicative resource in language, and it plays an important role in how news organisations and social media users inform, persuade and entertain their audiences. Stance may also be an indicator of the ‘fakeness’ of news. Indeed, previous research (Trnavac & Põldvere, 2024) has identified significant differences in evaluative language use between fake and genuine news in English; however, it is unclear how these differences are reflected across languages and cultures. Therefore, the present study sets out to compare and contrast the occurrence of a range of lexico-grammatical features of stance across English in the US, Norwegian in Norway and Russian in Russia, based on Biber (2006). The lexico-grammatical features are divided into major structural and pragmatic categories (e.g., adverbs expressing epistemic stance: certainly). The data are from three comparable corpora, collected from fact-checking websites covering news in the respective languages. Based on previous cross-linguistic research on stance in news discourse (Marin-Arrese, 2015), we expect there to be considerable differences across the three languages due to general differences in argumentative and persuasive style, as well as specific cultural characteristics associated with each country (e.g., varying levels of freedom of expression). References Biber, D. (2006) Stance in spoken and written university registers. Journal of English for Academic Purposes, 5, 97–116. https://doi.org/10.1016/j.jeap.2006.05.001 Marin-Arrese, J. I. (2015). Epistemicity and stance: A cross-linguistic study of epistemic stance strategies in journalistic discourse in English and Spanish. Discourse Studies, 17(2), 210–225. https://doi.org/10.1177/1461445614564523 Trnavac, R., & Põldvere, N. (2024). Investigating Appraisal and the language of evaluation in fake news corpora. Corpus Pragmatics. https://doi.org/10.1007/s41701-023-00162-x