Title Linguistic representation of muslim identity in the british media: a corpus-based study
Translation of Title Musulmonų tapatybės lingvistinė raiška Didžiosios Britanijos žiniasklaidoje: tekstynu paremtas tyrimas.
Authors Islam, Md Nymul
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Pages 121
Keywords [eng] Muslim identity, British media, corpus linguistics, Critical Discourse Analysis, framing, media representation, Sketch Engine musulmonų tapatybė, britų žiniasklaida, korpuso lingvistika, kritinė diskurso analizė, įrėminimas, žiniasklaidos reprezentacija, Sketch Engine
Abstract [eng] This study examines the linguistic representation of Muslim identity in the British media through a corpus-based approach using Sketch Engine. The corpus consists of 60 news articles and headlines from three major British news outlets: The Daily Mail, The Guardian, and the BBC. Two separate corpora were compiled: one for the news articles and one for the headlines, in order to examine the representational patterns at both the article level and the headline level independently. The study is based on Critical Discourse Analysis and framing theory, using Sketch Engine as a primary analytical tool. The study focuses on lexical choice and framing strategies across word frequency lists, adjective frequency lists, noun frequency lists, verb frequency lists, concordance lines, and a separate headline corpus. The findings of the study reveal that British media coverage about Muslim identity is dominated by two representational frames: a threat frame, which associates Muslims with danger, extremism, and state restriction, and a victimization frame, which associates Muslim identity with a target of discrimination and violence. The dominant lexical choices surrounding the node words "Muslim" and "Muslims" are consistently situated within semantic fields of security, violence, and institutional control. The study concludes that the language the British media use is not neutral. It reflects and reinforces certain views about who Muslims are and what role they play in British society.
Dissertation Institution Vilniaus universitetas.
Type Master thesis
Language English
Publication date 2026