Development of a mathematical model for the processes of researching citizen appeals

Currently, citizens actively participate in public discussions that affect the life of society. With the development of digitalization, users are increasingly using social networks and feedback platforms (FBPs) to express their opinions on various areas of activity. In this regard, there is a need to analyze public sentiment using modern analytical tools in order to identifypotential problems at an early stage. This article describes the development of a mathematical model for analyzing public sentiment based on text messages published on social networks and other sources. The model includes data preprocessing, clustering of requests, naming of clusters using language models, and summarization of identified problems.