Probabilistic Models of Psychological Aspects in Computer–based Social Interactions

The subject of the paper is the study of how to mathematically represent the phenomenon of the emergence of psychological and social situations in the process of interaction with various virtual objects, with an emphasis on the dangers that may arise in this interaction. These situations are considered in terms of emotions displayed by members of a social network, which, along with people interacting with computer interfaces, can also include avatars or bots.We argue that Markov chains, which are widely used for tasks of analyzing the optimization of social interaction (including such as interaction with humans and reactions of programs that support web navigation, interaction between humans and bots or between bots), do not reflect some aspects for which it is necessary to use such characteristics (concepts) as “speed” and “time”. More suitable are CTMC based models. A stochastic automaton network (SAN) is proposed as a high-level tool for representing the psychological interaction models described by CTMC.