The evolution of the lexical richness of the Russian language (corpus research based on diachronic datasets from the national corpus of the Russian language)
Abstract
Background. The relevance of this study is determined by the need to investigate lexical change in Russian using modern methods. The scientific novelty of the work lies in the development and application of complex statistical models and indices for a systematic quantitative analysis of Russian lexis based on new, previously unexplored material—frequency dictionaries for the periods 1700–1916, 1918–1991, and 1992–2016, with a total size of 250 million tokens. This made it possible to identify and quantitatively describe the dynamics of lexical richness and the structure of the vocabulary in a diachronic perspective.
Purpose. To determine the specific features of the dynamics of lexical richness in Russian on the basis of frequency dictionaries for the periods 1700–1916, 1918–1991, and 1992–2016.
Materials and methods. The material of the study consists of diachronic datasets of the Russian National Corpus for the periods 1700–1916, 1918–1991, and 1992–2016. The methods include computer-based corpus processing and testing for compliance with Zipf’s law, calculation of the Herfindahl–Hirschman Index (HHI), Simpson’s index, Berger–Parker index, Shannon entropy, the Type–Token Ratio (TTR) as a coefficient of lexical diversity, chi-square tests of statistical significance, and other related measures.
Results. Corpus-based analysis of diachronic data for the periods 1700–1916, 1918–1991, and 1992–2016 revealed a decrease in the overall lexical diversity and richness of Russian from the pre-revolutionary to the post-Soviet period. However, this lexical impoverishment occurs mainly at the expense of rare and low-frequency words, whereas the active vocabulary, by contrast, expands and becomes more productive.
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References
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Национальный корпус русского языка (НКРЯ) [Электронный ресурс]. (2003–2025). Скачиваемые корпуса. Получено 19.10.2025, из: https://ruscorpora.ru/page/corpora-datasets/
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Kutuzov, A., & Kuzmenko, E. (2018). Two centuries in two thousand words: Neural embedding models in detecting diachronic lexical changes. In: Quantitative approaches to the Russian language (pp. 95–112). Routledge. https://doi.org/10.4324/9781315105048-5
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Malvern, D., Richards, B., Chipere, N., & Durán, P. (2004). Lexical diversity and language development (pp. 16–30). Palgrave Macmillan UK.
MacKay, D. J. (2003). Information theory, inference and learning algorithms. Cambridge: Cambridge University Press.
Piperski, A. (2023). Lexical diversity of Russian poets. In: Literature, language and computing: Russian contribution (pp. 113–120). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-99-3604-5_10
Piantadosi, S. T. (2014). Zipf’s word frequency law in natural language: A critical review and future directions. Psychonomic Bulletin & Review, 21(5), 1112–1130. https://doi.org/10.3758/s13423-014-0585-6. EDN: https://elibrary.ru/SFDFMF
Rosillo Rodes, P., San Miguel, M., & Sánchez, D. (2025). Entropy and type token ratio in gigaword corpora. Physical Review Research, 7(3), 033054. https://doi.org/10.48550/arXiv.2411.10227. EDN: https://elibrary.ru/XQTDHY
Sherstinova, T., & Martynenko, G. (2019, November). Linguistic and stylistic parameters for the study of literary language in the corpus of Russian short stories of the first third of the 20th century. In: R. Piotrowski’s Readings in Language Engineering and Applied Linguistics: Proceedings of the III International Conference on Language Engineering and Applied Linguistics (PRLEAL 2019) (Saint Petersburg, Russia, pp. 105–120).
Song, J., & Lei, L. (2025). Lexical bloom, syntactic retreat: Examining complexity trade offs within Classical Chinese evolution across two millennia. Corpus Linguistics and Linguistic Theory. https://doi.org/10.1515/cllt-2024-0125. EDN: https://elibrary.ru/ZMAJJX
Zipf, G. K. (1972). Human behavior and the principle of least effort: An introduction to human ecology. Hafner.
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