The article discusses the use of stylometric1 analysis in plagiarism detection in texts in the Tatar language. Relevant tools have been developed, utilizing machine learning algorithms, including clustering (k‑means clustering), classification (random forest method, support vector machine method, naïve Bayes classifier), and a hybrid approach (FastText model + logistic regression). Special attention is paid to the adaptation of linguistic metrics to the Tatar language. The possibility is demonstrated of using stylometric analysis methods to address tasks of authorship attribution and determination of style and emotional tone in texts in the Tatar language.
Khayaleeva et al. (Mon,) studied this question.