This article is devoted to the study of adjectival collocations with the components ‘coronavirus’ and ‘COVID-19’ using the AntConc application. Collocations are considered as statistically stable combinations, both phraseologized and free. A technique for working with the AntConc for studying collocations has been developed. It includes four stages: 1) collecting empirical material; 2) uploading text collections into the service and setting parameters; 3) developing criteria for selecting units of analysis and its implementation; 4) analysing the material and describing the results. It has been found that ‘coronavirus’ lexemes tend to co-occur with 11 adjectives. Two lexical-syntactic models of compatibility of the lexemes ‘coronavirus’ and ‘COVID-19’ with adjectives have been identified. Testing of AntConc gave generally positive results. It allows the researchers to identify collocations, rank them by frequency or degree of typicality, observe specific use of collocations, and analyze their limitations. The advantages of AntConc also include the ability to independently select a research collection, an easy-to-use interface, and the ability to work with structures of varying complexity. However, researchers need to pay attention to the following drawbacks: a large amount of ‘noise’, impossibility to reduce all the identified word forms to a single lemma, inability to save texts in the program and to save sample results to text applications, inconvenience to copy examples directly from the application. The need to provide a sufficient collection of texts for research needs is emphasized. The application can be used both for research and working with students in corpus linguistics workshops.
|投稿的翻译标题||APPLICATION OF ANTCONC TO STUDY SYNTAGMATIC СO-OCCURRENCE (BASED ON ADJECTIVAL COLLOCATIONS WITH COMPONENTS ‘CORONAVIRUS’ AND ‘COVID-19’ IN FRENCH)|
|期刊||Вестник Пермского национального исследовательского политехнического университета. Проблемы языкознания и педагогики|
|州||Published - 2022|
- 16.00.00 LINGUISTICS
Level of Research Output
- VAK List