Linguistic repercussions of Covid-19
A corpus study on four languages
Bibliographic Data
| ID | 21240063 |
|---|---|
| Authors | Emmanuel Cartier (0000-0002-0469-4893, Sorbonne Université), Alexander Onysko (0000-0002-4879-3527, University of Klagenfurt, corresponding author), Esme Winter-Froemel (0000-0003-3437-8864, University of Würzburg), Eline Zenner (0000-0002-8114-5425, KU Leuven), Gisle Andersen (0000-0002-9585-9779, Norwegian School of Economics), Béryl Hilberink-Schulpen (0000-0002-7355-4712, Radboud University Nijmegen), Ulrike Nederstigt (0000-0003-0135-0144, Radboud University Nijmegen), Earl Peterson (0000-0002-6057-1804, University of Helsinki), Elizabeth Peterson (0000-0001-7436-3478, University of Helsinki), Frank Van Meurs (0000-0002-2099-4781, Radboud University Nijmegen) |
| Year | 2022 |
| Volume | 8 |
| Issue | 1 |
| Pages | 751-766 |
| Publication date | 2022-12-05 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Open Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 2300-9969 • E-ISSN: 2300-9969 |
| Publisher | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/opli-2022-0222 |
| OpenAlex | W4312685733 |
| Language | EN |
| References cited | 31 |
The global reach of the COVID-19 pandemic and the ensuing localized policy reactions provides a case to uncover how a global crisis translates into linguistic discourse. Based on the JSI Timestamped Web Corpora that are automatically POS-tagged and accessible via SketchEngine, this study compares French, German, Dutch, and English. After identifying the main names used to denote the virus and its disease, we extracted a total of 1,697 associated terms (according to logDice values) retrieved from news media data from January through October 2020. These associated words were then organized into categories describing the properties of the virus and the disease, their spatio-temporal features and their cause–effect dependencies. Analyzing the output cross-linguistically and across the first 10 months of the pandemic, a fairly stable semantic discourse space is found within and across each of the four languages, with an overall clear preference for visual and biomedical features as associated terms, though significant diatopic and diachronic shifts in the discourse space are also attested
Disease · German · Linguistics · Pandemic · Preference · Sociology · Computer Science · History · Language, Metaphor, and Cognition · linguistics and terminology studies · Linguistics, Language Diversity, and Identity · Mathematics · Medicine · Philosophy
Framing Covid-19
Creating Covid-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter
Sentiments and emotions evoked by news headlines of coronavirus disease (Covid-19) outbreak
Novel Coronavirus (Covid-19) Pandemic
Coronavirus
“Not Soldiers but Fire-fighters” – Metaphors and Covid-19
Une étude de sémantique historique du mot confinement
Covid-19 Insights and Linguistic Methods
English-based coroneologisms
The Sketch Engine
Pandemic and its metaphors
Diaspora micro-influencers and Covid-19 communication on social media
Fighting Covid-19 in East Asia
Linguistic diversity in a time of crisis
Countering Covid-19-related anti-Chinese racism with translanguaged swearing on social media
Pandemic discourses and the prefiguration of the future
Communicability, stigma, and xenophobia during the Covid-19 outbreak
The return of the ‘Yellow Peril’
I don’t feel like talking about it”
Fighting Covid-19 with Mongolian fiddle stories
| Citation velocity | historical |
|---|---|
| Highly cited | No |