Abstract
Fake news poses a significant threat to society by undermining public trust and consensus on critical issues. Although there is a considerable amount of research on the linguistic features of fake news texts, a comprehensive understanding of how language is used to persuade and promote specific ideologies within them is still lacking. This study addresses this gap by analyzing fake news discourse through the lens of news values. We apply the Discursive News Values Analysis (DNVA) framework and key semantic domain analysis to a corpus of fake news stories on vaccination, climate change, and COVID-19. We identify a set of news values that differentiate fake from mainstream news discourse. Our findings reveal that fake news emphasizes negativity, unexpectedness, consonance, and facticity, while also relying on the previously undocumented news values of subversiveness, causality, religiosity, and historicity. These values form a powerful discursive toolkit exploited by fake news writers to craft compelling false narratives.
| Original language | English |
|---|---|
| Journal | Discourse and Communication |
| Publication status | Accepted/In press - 17 Aug 2024 |
Bibliographical note
Not yet published as of 10/09/2024.Keywords
- disinformation
- newsworthiness
- polarization
- corpus-assisted discourse analysis
- semantic tagging
Access to Document
- BaissaB2024news
This document is the Author Accepted Manuscript version of a work which will appear in its final form in Discourse & Communication. The final Version of Record will be available at: https://journals.sagepub.com/home/dcm.