JOURNAL ARTICLE
The British Online Media's Representation of the George Floyd Anti-Racism Protests from his Murder in May 2020 until May 2021.
Published In: Journal of Language & Discrimination, 2025, v. 9, n. 1. P. 136 1 of 3
Database: Communication Source 2 of 3
Authored By: Chichon, Jagon 3 of 3
Abstract
This article analyzes the framing of the 2020 George Floyd protests in the headlines, subheadings, summaries, and captions of three UK-based online news outlets: the Mail Online (right-wing), the Guardian Online (left-wing), and BBC News Online (broadly impartial). Using a qualitative linguistic and syntactic analysis grounded in social semiotics and functional grammar, it identifies differences in how these publications portray the protests, focusing on references to conflict or peacefulness, predicational strategies (actions attributed to protesters), the cause of the protests, and referentials (naming of protesters). The Mail’s coverage emphasizes conflict, violence, and criminality linked implicitly to anti-racism protesters while explicitly foregrounding the specifics of George Floyd’s murder by American police, thereby legitimizing the protests’ cause but framing UK protesters as an external threat. In contrast, the Guardian and BBC depict protesters engaging in normative, peaceful actions, background conflict, and often omit explicit mention of police culpability in Floyd’s death, reflecting ideological orientations and differing editorial policies within the UK media context. The study highlights how ideological stance, political proximity, and media format influence the representation of social movements in online news discourse.
Additional Information
- Source:Journal of Language & Discrimination. 2025/01, Vol. 9, Issue 1, p136
- Document Type:Article
- Subject Area:Political Science
- Publication Date:2025
- ISSN:2397-2637
- DOI:10.3138/jld-2025-0506
- Accession Number:186778624
- Copyright Statement:Copyright of Journal of Language & Discrimination is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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