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- Title
Denominative variation in the COVID-19 Open Research Dataset corpus.
- Authors
Benítez Carrasco, Valeria; León-Araúz, Pilar
- Abstract
Since 2020, we have witnessed the emergence of new concepts and terms due to the pandemic outbreak. Some of them have even become obsolete in a short period of time whereas others are still misused despite standardization efforts. In this paper we study explicit denominative variation in the COVID-19 corpus, which consists of scientific articles released as part of the COVID-19 Open Research Dataset and is publicly available in Sketch Engine. First of all, variants for severe acute respiratory syndrome coronavirus 2 and coronavirus disease 2019 were extracted by means of knowledge patterns (e.g., also known as). The productiveness of knowledge patterns was analyzed and a set of 1,684 explicit variation excerpts were collected and manually annotated. A total of 371 variants were retrieved and organized in two polydenominative clusters (i.e., 177 for COVID-19 and 193 for SARS-CoV-2), which were then formally and semantically characterized by comparison with the established designations. Finally, possible causes underlying denominative variation are explored.
- Subjects
SARS-CoV-2; OPEN scholarship; COVID-19
- Publication
Terminology, 2023, Vol 29, Issue 2, p252
- ISSN
0929-9971
- Publication type
Article
- DOI
10.1075/term.00071.ben