Shaban, Saif Abdulkareem H. and Al-Asadi, Rusul Adnan N. (2026) The Representation of the White Army in Social Media Posts: Critical Discourse Analysis. CENTRAL ASIAN JOURNAL OF LITERATURE, PHILOSOPHY, AND CULTURE, 7 (3). pp. 257-267. ISSN 2660-6828

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Abstract

During the years of the pandemic (2020-2022), the efforts of the medical group adopted a new approach. They played an essential role in the process of fighting COVID-19. People tried to thank, encourage, and support them by using language tools. The current research presented a study in critical discourse analysis to investigate the texts that people used, whether to thank, describe, or encourage the members of the medical field during the war against COVID-19.This work aims to investigate the linguistic devices used in Facebook posts concerning vocabulary and text structure to praise the medical crews during the pandemic, deconstruct the mental models that led those people publish to publish such posts, and interpret how this digital discourse contributes to reshaping the social image of the medical crews. Furthermore, this study analyzed five discourses, posts published on the Facebook social media platform, based on levels put forward by linguists specialized in critical discourse analysis, such as Norman Fairclough and van Dijk. Finally, the current research concluded that the posts employ several metaphorical expressions, such as the knight and the army of mercy. Besides, the text structure of these discourses, was categorized by strong coherence and clear logical reasoning. The language used to praise the medical crews was not spontaneous, but rather depended on intensive linguistic tactics that transformed doctors and other medical staff from the medical lexicon into the military field. Finally, the study demonstrated that the tribute phrases used contributed to redesigning the social identity of the medical members. Doctors and other medical staff were shifted from specialized employees into heroes and social leaders.

Item Type:	Article
Subjects:	A General Works > AI Indexes (General)
Depositing User:	admin eprints
Date Deposited:	17 Jun 2026 14:47
Last Modified:	17 Jun 2026 14:47
URI:	http://eprints.umsida.ac.id/id/eprint/16596

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