AI Based Mental Health Detection Via Social Media Analysis

The proposed AI-based mental health detection system successfully analyzes social media text to identify emotional patterns and potential mental health conditions. By integrating Natural Language Processing (NLP) with machine learning and deep learning models such as CNN, RNN, LSTM, BERT, and Decision Tree, the system provides accurate and reliable predictions. The implementation demonstrates that advanced models, particularly BERT and LSTM, achieve higher accuracy due to their ability to capture contextual and sequential information from text. The system effectively classifies emotions and determines risk levels based on user input, making it suitable for real-time analysis. Overall, the system provides a scalable and efficient solution for early detection of mental health issues. It can assist researchers, healthcare professionals, and organizations in improving mental health awareness and enabling timely intervention  

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