Representation of Muslims through Passivization and Nominalization in British News Media Discourse: The Times Online Newspaper as a Case Study
This paper investigates the way passivization and nominalization are used to represent Muslims in the language of one of the most prominent British online newspapers, The Times. The study, which adopts the Critical Discourse Analysis approach, aims to achieve this objective by comparing the way Musl...
Authors: | ; |
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Format: | Electronic Article |
Language: | English |
Check availability: | HBZ Gateway |
Journals Online & Print: | |
Fernleihe: | Fernleihe für die Fachinformationsdienste |
Published: |
Routledge, part of the Taylor & Francis Group
2021
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In: |
Journal of Muslim minority affairs
Year: 2021, Volume: 41, Issue: 4, Pages: 685-702 |
Further subjects: | B
online newspapers
B Islam B passivization B Critical Discourse Analysis B media discourse B Representations B nominalization |
Online Access: |
Volltext (lizenzpflichtig) |
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520 | |a This paper investigates the way passivization and nominalization are used to represent Muslims in the language of one of the most prominent British online newspapers, The Times. The study, which adopts the Critical Discourse Analysis approach, aims to achieve this objective by comparing the way Muslim and non-Muslim subjects are talked about, to eventually see if there is any differential treatment in the discourse of the newspaper under investigation. The study analyses ten randomly selected news articles reporting stories about shootings and bombings, which got a substantial amount of media coverage. The results show that passivization is used more frequently in the articles about non-Muslim attackers, while nominalization displays a different pattern by being used more frequently in the articles talking about Muslim subjects. The way Muslim subjects are represented in the newspaper texts is believed to contribute to the reinforcement of some negative and widespread stereotypical images about Muslims and Islam. | ||
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650 | 4 | |a Critical Discourse Analysis | |
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