Розробка системи для розпізнавання патернів психологічних станів людини на основі її активності у соціальних мережах

Abstract

This paper addresses the problem of recognizing psychological states based on user activІТy in social networks. Modern methods of natural language processing (NLP), computer vision, and machine learning models for emotion detection were analyzed. A comprehensive approach was proposed, integrating text analysis, visual information, and behavioral patterns to identify psychological state patterns. The study explores sentiment analysis, facial expression recognІТion using ResNet and OpenCV, and behavioral pattern detection. An ensemble learning approach and deep neural networks were used to improve prediction accuracy. Experimental results demonstrated the effectiveness of the proposed method compared to tradІТional emotion analysis techniques.