Depression Intensity Prediction and Prevention via Social Media

Abstract

Social media platforms often reflect users’ emotional and mental health states, making them valuable for analyzing conditions like depression. This project, “Depression Intensity Estimation via Social Media – A Deep Learning Approach”, applies advanced NLP and deep learning techniques to detect and classify depression severity from user posts on platforms such as Twitter and Reddit. By leveraging pre-trained language models and contextual embeddings, the system categorizes posts into mild, moderate, or severe levels. The model is trained on annotated datasets and evaluated using standard metrics, with explainability features highlighting key linguistic cues. This research demonstrates the potential of AI-based, non-invasive tools for scalable mental health monitoring and early intervention.