Adaptive Intervention Architecture for Psychological Manipulation Detection: A Culture-Specific Approach for Adolescent Digital Communications

This study introduces a novel artificial intelligence system for detecting and addressing psychological manipulation in digital communications, with a focus on adolescents. The system integrates a hybrid neural network model with emotion analysis capabilities specifically designed for Korean language contexts. Our approach combines text analysis with emotion recognition to enhance detection accuracy while implementing a tiered intervention strategy based on risk levels. The system demonstrated significant improvements over baseline models in detecting various forms of psychological manipulation, particularly in identifying subtle patterns. Our expert evaluation suggests the system’s potential effectiveness in protecting adolescent mental health in digital environments. While primarily focused on adolescents, the findings indicate broader applicability across age groups. This research contributes to the field by offering a culturally adapted framework for psychological manipulation detection, a multimodal analytical approach, and an ethically designed intervention system.