Image of “Snake flu,” “killer bug,” and “Chinese virus”: A corpus-assisted critical discourse analysis of lexical choices in early UK press coverage of the COVID-19 pandemic

Text

“Snake flu,” “killer bug,” and “Chinese virus”: A corpus-assisted critical discourse analysis of lexical choices in early UK press coverage of the COVID-19 pandemic



Now mostly known as “COVID-19” (or simply “Covid”), early discourse around the pandemic was characterized by a particularly large variation in naming choices (ranging from “new coronavirus” and “new respiratory disease” to “killer bug” and the racist term “Chinese virus”). The current study is situated within corpus-assisted discourse studies and analyses these naming choices in UK newspaper coverage (January–March 2020), focusing on terminology deemed “inappropriate” as per WHO guidelines on naming infectious diseases. The results show that 9% of all terms referring to COVID-19 or the virus causing it are “inappropriate” overall, with “inappropriate” naming being more prevalent (1) in tabloids than broadsheets and (2) in the period before compared to the period after the virus was ocially named on 11th February, 2020. Selected examples within each of the categories of “inappropriate” names are explored in more detail [terms (1) inciting undue fear, (2) containing geographic locations, and (3) containing species of animals], and the findings are discussed with regard to the contribution of lexical choices to the reproduction of (racist and otherwise problematic) ideologies in mainstream media.


Availability

No copy data


Detail Information

Series Title
-
Call Number
-
Publisher Frontiers in Artificial Intelligence : Switzerland.,
Collation
006
Language
English
ISBN/ISSN
2624-8212
Classification
NONE
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Specific Detail Info
-
Statement of Responsibility

Other Information

Accreditation
Scopus Q3

Other version/related

No other version available


File Attachment



Information


Web Online Public Access Catalog - Use the search options to find documents quickly