Trump and muslims: A critical discourse analysis of islamophobic rhetoric in Donald Trump's selected tweets

Khan, Mohsin Hassan and Qazalbash, Farwa and Adnan, Hamedi Mohd and Yaqin, Lalu Nurul and Khuhro, Rashid Ali (2021) Trump and muslims: A critical discourse analysis of islamophobic rhetoric in Donald Trump's selected tweets. SAGE Open, 11 (1). ISSN 2158-2440, DOI https://doi.org/10.1177/21582440211004172.

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Abstract

The emergence of Donald Trump as an anti-Muslim-Islam presidential candidate and victory over Hillary Clinton is an issue of debate and division in the United States' political sphere. Many commentators and political pundits criticize Trump for his disparaging rhetoric on Twitter and present him as an example of how Twitter can be an effective tool for the construction and extension of political polarization. The current study analyzes the selected tweets by Donald Trump posted on Twitter to unmask how he uses language to construct Islamophobic discourse structures and attempts to form his ideological structures along with. The researchers hypothesize that Islamophobia is a marked feature of Trump's political career realized by specific rhetorical and discursive devices. Therefore, the study purposively takes 40 most controversial tweets of Donald Trump against Islam and Muslims and carried out a critical discourse analysis with the help of macro-strategies of the discourse given by Wodak and Meyer and van Dijk's referential strategies of political discourse. The findings reveal that Trump uses language rhetorically to exclude people of different ethnic identities, especially Muslims, through demagogic language to create a difference of ``us'' vs. ``them'' and making in this way ``America Great Again''.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: Donald Trump; US 2016 presidential elections; Twitter; Islamophobia; critical discourse studies; us versus them
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 29 Jul 2022 02:08
Last Modified: 29 Jul 2022 02:08
URI: http://eprints.um.edu.my/id/eprint/28152

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