This study is situated at the intersection of corpus linguistics and terminology studies. It highlights the significant evolution of corpus linguistics, from early text collections to the establishment of large national and specialized corpora in the 21st century. The importance of contemporary technologies, such as machine learning and natural language processing, is emphasized for their role in opening new avenues for analyzing large data sets. The article addresses the methodological aspects of researching terminological units within the field of artificial intelligence (AI) based on modern analytical compilations. The aim of the research is to identify patterns in the formation of compound designations, as well as the orthographic and stylistic norms governing the use of AI terms in the Russian language. To achieve this goal, frequency analysis and content analysis methods were employed using AntConc, resulting in the identification of 100 core terms, along with collocations constructed from these terms. The findings indicate that AI terminology in Russian is actively evolving, with a predominance of Anglicisms and hybrid forms. The stylistic features of texts reflecting the technical context and target audience are discussed. In conclusion, the necessity for establishing norms for the use of AI terms in light of their integration into the Russian language is underscored.
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O. V. Shadrina
Oksana Marunevich
Nauchnyi Dialog
Moscow Institute of Physics and Technology
Moscow Power Engineering Institute
Moscow Aviation Institute
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Analyzing shared references across papers
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Shadrina et al. (Mon,) studied this question.
www.synapsesocial.com/papers/68de79715b556a9128e1b19f — DOI: https://doi.org/10.24224/2227-1295-2025-14-7-133-160