INTELLIGENT SYSTEM FOR SENTIMENT ANALYSIS AND CLUSTERING OF PUBLICATIONS WITHIN THE SOCIAL NETWORK OF TWITTER

Анотація

The development and implementation of an intelligent system for analyzing the sentiment and organizing publications is a relevant and promising task. In today's world, social networks serve as the primary means of communication, reflecting various situations and circumstances. Each user's message within a social network carries specific semantics, reflecting their thoughts, analysis of the relevant situation, or reactions to specific events. Advanced algorithms and data analysis approaches [1] now enable efficient and straightforward analysis of large volumes of textual data. This enables the determination of the average sentiment expressed by users towards specific events and allows drawing conclusions based on the analyzed content. Consequently, it becomes possible to understand the attitudes of different user groups towards various types of content, offers, goods, and market offerings. Major brands and corporations actively employ these approaches to analyze information, determining the sentiment of user texts and dividing them, along with the users themselves, into clusters for further analysis and engagement.