Open AccessAnalysing Academic Texts with Computational Linguistics Tools
Author(s) -
Elena I. Shpit,
В. Н. Куровский
Publication year - 2020
Publication title -
vysšee obrazovanie v rossii
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.292
H-Index - 8
eISSN - 2072-0459
pISSN - 0869-3617
DOI - 10.31992/0869-3617-2020-29-7-89-103
Subject(s) - computer science , sentence , computational linguistics , corpus linguistics , applied linguistics , linguistics , academic writing , genre analysis , natural language processing , software , artificial intelligence , programming language , philosophy
Writing academic texts in English introduces certain difficulties associated with translating Russian sentences with pronounced stylistic peculiarities, especially for young researchers who are just starting their publication activity. It seems impossible to study any genre without analysing examples of the discourse, which highlights the use of computational linguistics as it allows automating a lot of language and text processing mechanisms and generates relatively accurate quantitative results. The present study considers the application of AntConc and Coh-Metrix toolkits for analyzing master students’ abstracts to research papers written for international English-language journals or conference proceedings (Learner Corpus) in comparison with international researchers’ abstracts published in high-impact journals (Reference Corpus). The analysis conducted in the above-mentioned software tools revealed the drawbacks and strengths of master students’ texts, allowed characterizing them on the words, sentence and discourse levels, as well as outlined the potentials of their use in teaching academic writing skills.