| Author: | Zhao, Ruinan |
| Title: | Competing discursive constructions of Covid-19 vaccines : a corpus-assisted discourse study |
| Advisors: | Liu, Ming (CBS) |
| Degree: | DALS |
| Year: | 2023 |
| Subject: | Critical discourse analysis Discourse analysis -- Political aspects Newspapers -- Language COVID-19 (Disease) -- Vaccination COVID-19 (Disease) -- Economic aspects Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Humanities |
| Pages: | xii, 265 pages : color illustrations |
| Language: | English |
| Abstract: | It has now been widely acknowledged that COVID-19 vaccine development and communication is not only a pure scientific issue but also a political issue due to the contentious nature of the effects of COVID-19 vaccines and the immense economic and political interests involved. This study combines the theories and methods of critical discourse analysis (CDA) and corpus linguistics (CL) to give a corpus-assisted discourse study (CADS) of the representations of COVID-19 vaccines in three English-language newspapers published in the U.S., Hong Kong, and Chinese mainland to reveal their preferential ways of representing COVID-19 vaccines and explicate the dynamic relations between vaccines, media, and politics. Three corpora are built by collecting all news articles related to COVID-19 vaccines from 1 January 2020 to 30 September 2021 in China Daily (CD), The New York Times (NYT), and South China Morning Post (SCMP). With an integrated analytic framework, this study gives a close analysis of the representations of COVID-19 vaccines at different levels, including topics/themes/frames, discursive strategies, and linguistic means and realizations. It presents not only the overall analysis of the representations of COVIDÂ-19 vaccines but also the particular ways of representing the safety, efficacy, and risks of COVID-19 vaccines. The findings reveal varied pictures in the three newspapers’ representations of COVID-19 vaccines. CD aligns with the Chinese government and national interests by adopting an overwhelming gain frame in vaccine representation and giving the most positive coverage of Chinese COVID-19 vaccines with a view to appeasing public fears and persuading them into taking vaccination. It features globalism as it tries to promote collaboration in vaccine development and distribution. NYT aligns with its national interests by underlining the efficacy of US vaccines and the safety of American people on the one hand and the journalistic norm of balanced reporting by presenting both positive and negative representations of COVID-19 vaccines. It features nationalism by underlining the national interests of the US, to the ignorance of its global responsibilities in developing and distributing COVID-19 vaccines. SCMP, by contrast, also aligns with Hong Kong government to show preferences for gain frame over loss frame by giving more positive representations of COVID-19 vaccines with a view to persuading the public into taking vaccination. Nevertheless, it also aligns with the public to give a negative representation of Chinese vaccines and a positive representation of Western vaccines. It also features globalism by highlighting the global access to the COVID-19 vaccines developed in the US. A corpus-assisted discourse study of the representations of COVID-19 vaccines can reveal not only the particular ways of representing COVID-19 vaccines, but, more importantly, the dynamics between vaccine, media and politics. It can contribute to previous studies on COVID-19 vaccine communication by presenting a multi-dimensional and multi-faceted analysis of the media discourse with the help of computer-assisted corpus-analytic tools. This study sheds light on the significance of the critical reading of vaccine media discourse in different socio-political contexts and the integrated analytic framework established in this study can contribute to more studies towards this endeavor. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 7168.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.79 MB | Adobe PDF | View/Open |
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