Analyzing Emotional Dynamics in Online Psychological Counseling Communities: An NLP and Database Approach for Mental Health Support
Qingyue KongAbstract
Objective
This study aims to investigate the emotional patterns and psychological support mechanisms in online mental health communities through natural language processing and database technologies. The research seeks to identify key emotional characteristics and interaction dynamics that contribute to effective psychological support, providing evidence-based insights for improving digital mental health services.
Subjects and Methods
The study collected 158,642 anonymous posts from a major Chinese online psychological counseling platform over a 12-month period. Using natural language processing techniques including BERT-based sentiment analysis and LDA topic modeling, we analyzed emotional expressions and content themes. Database technologies were employed for large-scale data management and pattern identification. Psychological scales including the Psychological Stress Scale and Social Support Rating Scale were used as validation metrics.
Results
The analysis revealed significant emotional patterns, with 68.3% of posts showing improved emotional scores after community interaction. Help-seeking posts were predominantly characterized by anxiety (42.1%) and depression (35.7%) related content. Supportive responses significantly correlated with poster's emotional improvement (r = 0.73, p < 0.01). The NLP model achieved 89.2% accuracy in identifying crisis-level posts requiring professional intervention. Temporal analysis showed distinct diurnal patterns in emotional expression intensity.
Conclusions
Online psychological communities serve as effective emotional support spaces, with natural language processing providing valuable tools for monitoring and enhancing support quality. The integration of database technologies enables real-time emotional state assessment and crisis detection. These findings support the development of AI-enhanced mental health platforms that can provide timely, personalized psychological support while maintaining professional oversight.
Corresponding Author
Qingyue Kong, Department of information engineering Hebei Chemical & Pharmaceutical College, Shijiazhuang, Hebei, 050026, China.