text classification

The results of research into the process of grouping authors of printed text messages in social networks are presented. The hypothesis about the possibility of grouping authors based on the results of the classification of their text messages has been confirmed. For this purpose, the virtual robot builds an intelligent monitoring agent for grouping the authors of social network text messages. The peculiarity of these messages is that they are short texts.

In the digital age, the significant increase in information generation and processing is accompanied by a growing threat of unauthorized access, illegal distribution, and use. One of the most promising strategies for protecting information from various cyber threats and malicious attacks is the use of Natural Language Processing (NLP) processors. This article focuses on the methodology of data protection in the context of utilizing Natural Language Processing for sentiment analysis and trend detection.

The article addresses the problem of text classification in the context of growing information flows and the need for automated content analysis. A universal information technology is proposed, combining classical machine learning methods with the potential of Large Language Models for processing news, scientific, literary, journalistic and legal texts. Using the BBC News corpus (2225 texts), k-means clustering with TF-IDF demonstrated clear thematic grouping.

Розглянуто класифікацію повідомлень груп новин у просторі семантичних полів. Проаналізовано ефективність баєсівського класифікатора та класифікатора за найближчими сусідами для різних навчальних та тестових вибірок повідомлень. Показано існування підмножини груп новин, для яких використання аналізованих класифікаторів є ефективним.