The results of research into the process of grouping authors of printed text messages in social networks are presented. The hypothesis about the possibility of grouping authors based on the results of the classification of their text messages has been confirmed. For this purpose, the virtual robot builds an intelligent monitoring agent for grouping the authors of social network text messages. The peculiarity of these messages is that they are short texts. In this regard, machine learning of classifier models was carried out on observation points that described message windows of 100 characters. In the process of this training, the method of profiled formation of the primary description of the text message is used. The structure of a virtual robot that performed the monitoring task of grouping authors with common properties is described. An example of building a structural element of a virtual robot - an agent model of a classifier is given. Messages from two authors belonging to one of the expertly created classes were used as a benchmark. The analysis of the results of the work of the virtual robot allows us to state that the authors whose texts are recognized as similar to the standard have similarities in the form and content of their statements. The results of the research can be used to identify groups of authors who engage in joint destructive activities in social networks to the detriment of Ukraine (trolls).
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