AI-Driven Mental Health Chatbot for Emotion Recognition and Personalized Support

Many more students are struggling with mental health-related challenges including stress, anxiety, and depression. There is an ever-growing need for scalable, accessible solutions. Text-based chatbots have proven to be a very viable source that can provide immediate emotional support and interventions. This report is about a proposed system of a mental health chatbot that uses simple natural language processing. The chatbot would understand the inputs coming from the user, detect the emotional state, and make responses according to the set rules with sentiment analysis. Relatively lightweight and easy to deploy, it would run on multiple platforms, although concerned with real-time support. Utilizing large mental health datasets and NLP models, this chatbot would aid the users in managing their mental well-being by timely advice about alternative resources and healthy coping strategies. However, there are certain regions in this process that require development for effective support to the users, which includes the detection depth of emotion, personalization, and crisis management protocols.