machine learning.

Today, the potential of social networks for all types of communication is difficult to overestimate. For business communication in virtual communities, it is important to take into account the socio-psychological features of the participants in the communication process. This actualized various aspects of network identity, virtual personality behavior, and online persona. This study offers a review of the scientific literature on personality prediction based on the analysis of different content generated in social networks.

For the first time, it was proposed to use the information technology of intellectual monitoring to classify the authors of printed texts by sociotypes. The relevance of the work is determined by the need to automate the processes of describing the properties of the authors of messages, in particular in social networks, in order to develop controlling influences on a group of individuals and individuals. There is a relatively detailed description of the properties of a person belonging to one or another sociotype. This allows for the development of effective management influences.