Abstract
The article builds on the well-developed problem of studying trust in society towards social institutions, as well as between individuals. Currently, contact quantitative sociology faces a number of challenges, and the level of consent to participate in surveys is steadily falling. In order to reliably assess public opinion, non-contact tools for studying the digital environment are already required. The application of non-survey techniques for collecting big data using a pre-formed thesaurus allows us to select data for analysis and circumvent the problems associated with respondent recruitment. The application of SML approach to analyze digital publications of Russian-speaking users from Novosibirsk (more than 450 thousand publications) collected in 2020 has been considered. The combination of quantitative and qualitative methods allowed us to describe the audience and categorize the areas of public distrust and dissatisfaction. The application of this approach can be useful for managerial tasks aimed at increasing trust in society. Thus, the study is a valuable contribution to the development of modern sociology and its applied aspects.
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