ANALYSIS OF USER ACTIVITY ON THE INTERNET AS A TOOL FOR IDENTIFYING MENTAL DISORDERS IN INDIVIDUALS

Research on the mutual impact of the Internet and mental health is frequent, due to the increasing prevalence of both. Researchers have studied both negative and positive impacts, but little attention has been paid to studying the Internet as a tool for identifying, predicting and treating mental health disorders. The aim of this paper is to examine and analyse the literature on the use of the internet as a tool for identifying mental disorders from 2017 to 2022. A qualitative subject field review using the Scopus platform for information sources and VOSViewer for keyword visualisation was conducted to investigate this field. A total of 178 articles were selected, of which 23 fit all conditions and were carefully analysed. As a result, the main diseases for which the construction of mathematical models using machine learning for identifying and predicting depression using the lexical set and visual characteristics of human social media content have been identified. Articles were also found that use the resulting lexical set to create a comfortable online community for people suffering from mental disorders. The analysis demonstrates the following research gaps: lack of a universal model for identifying the disorder, small set of social networks. These shortcomings make it necessary to focus on this topic and to monitor its development in relation to the general digitalisation of society. The results of this review can be useful for the professionals dealing with the problem.