Negative Influences Exposure in Social Internet-services

Having regard to the last events in our country, it is possible to assert that network the Internet gradually became the source of threats to informative safety of man, society, state, as distribution in the global network of doubtful and biased content together with technologies of informatively-psychological influence on consciousness of individuals can assist an origin in society of dissatisfaction by operating state power, international conflicts, social aggression and others like that. The purpose of the article is to review method oriented to increase authenticity exposure negative informatively-psychological influence in social internet-service by realization automated analysis text content. Research methods. During research the methods of theory of social networks analysis (Social Network Analysis, SNA), methods of treatment of human language (Natural Language Processing, NLP), and methods of machine studies (Machine Learning), including deep studies (Deep Learning) have been used. The scientific novelty of the got results consists in that in-process first the method of application of deep studies models offers to the analysis task of the key in text data that differs from existing structure, which allows promoting exactness of informatively-psychological influences exposure in content of social networks. Conclusions. Research results can be drawn on at further development of facilities in the automated negative informatively-psychological influences exposure