The first part of the work conceptually examines applications of artificial intelligence in socio-humanitarian studies. The world trend of the last decades is focused on the involvement of social media data for research interests, which allows solving the tasks of monitoring, analysis, forecasting and management in relation to such parameters of network communication as opinions, attitudes, emotions, and behavior patterns of communicants. In order to develop tools for network content analysis, we propose to utilize the method for relational-situational analysis that based on the syntactic analysis approach by G.A. Zolotova and the concept of heterogeneous semantic networks proposed by G.S. Osipov. The proposed approach makes it possible to consider texts as the product of the author's speech-thinking activity, which allows applying Russian psychological research background to study cognitive processes, personality, motivation, emotional states, individual differences, and the general worldview.
PDF at SpringerLink: https://link.springer.com/content/pdf/10.3103/S0147688220060015.pdf
Yenikolopov, S. N., Kuznetsova, Y. M., Smyrnov, I. V., Stankevich, M. A., Chudova, N. V. Creating an automatic text analysis tool for the benefit of social and humanitarian research. Part 1. Methodological and methodological aspects // Artificial intelligence and decision-making. - 2019. - №. 2. – Page 28-38.