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Using a tool for automatic text analysis and machine learning methods developed at the Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, the first results are obtained in the task of identifying text parameters specific to people with certain psychological characteristics. The tool of corpus linguistic and statistical research, based on the use of relational-situational analysis, psycholinguistic indicators and dictionaries covering the vocabulary of emotional and rational assessment, allowed us to obtain values for 177 textual attributes of the essay written by 486 subjects. To obtain data on the severity of characterological and personality characteristics of the subjects, a number of psychological questionnaires were used. When processing the data, binary classification algorithms were used — the support vector method (SVM) and the Random Forest method. The results allow us to draw conclusions about the prospects of using some textual parameters in problems of population psychodiagnostics and the adequacy of the applied classification algorithms.

One of the psychological effects of digitalization is the establishment of specific relationships between a person and the cyber environment and its components. The paper presents the results of a study of the emotional component of attitudes towards the components of the digital environment, carried out using emotive-predicate analysis, a new method of computer text processing implemented in TITANIS, an advanced social media text analysis tool. Using this method, it is possible to automatically extract descriptions of emotional situations from texts in which the components of the digital environment are the cause or subject of 68 emotional states. The texts of 2048 online videos posted in the Russian-language segment of YouTube served as the material for the analysis. According to the frequency of occurrence, emotional situations involving various components of the digital environment are quite typical for even thematically irrelevant online discussions. The components of the digital environment mentioned in non-thematic discussions as participants in emotional situations are classified into the following three groups: (1) general concepts of digital technologies; (2) digital devices; (3) activities mediated by digital technologies. The lexemes of the latter group, denoting various aspects of network communication, are included in the vast majority of descriptions of emotional situations involving the components of the digital environment, and six times more often as causes of emotions than as subjects of emotional states. In general, the emotional attitude towards the components of the cyber environment as a whole is characterized as balanced, without a noticeable predominance of negative or positive emotions. However, negative states are more often attributed to the components of the cyber environment as the subjects than as the causes of emotions. The practical significance of the described method of text analysis as a means of assessing the emotional component of attitudes towards the components of the digital environment is determined by the influence that affective reactions of users have on the demand for technical innovations and the direction of their development.

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