Abstract
The article aims at considering stylometry automation of philological studies. The relevance of this article stems from the need to trace and critically analyze the results of numerous studies in the interdisciplinary field that have been actively developed in recent years to identify the author of the text using artificial intelligence methods (authorship attribution and profiling) as well as to provide theoretical foundations and a comprehensive stylometric methodology (i.e. based on the analysis of quantifiable linguistic features using statistical methods and machine learning algorithms) to identify the author of the text, based on the principles of explanation, objectivity, evidence, and open science. Within the framework of subject and activity identification idiolectology - is a developing scientific direction that focuses specifically on the systematic study of the phenomenon of idiolect in the identification of computer aspects using modern achievements of computational and corpus linguistics, and data science. The authors of the article claim that the task of computational and corpus linguistics is to provide the researcher with all the necessary material, to prepare the data for counting, and to offer a wide range of computational procedures that can be used to test hypotheses, together to confirm or refute ever subtler and profound philological observations. Philological problems, in solution of which language information is used, usually have, a clear application, orientation, the language, and style of the text in such a situation are not the goal of the study, but a means of solving extra-linguistic problems. The solution of a specific philological problem (e.g., the problem of disputed authorship) is usually not limited to the rigid framework of a particular research methodology but is carried out using methods and facts in various fields of knowledge and practical activities.