International Journal of Advanced Research in Computer and Communication Engineering

Abstract: This project presents a web-based AI-powered mental health analysis system designed to identify depression intensity from user-provided text. The system analyzes written content such as personal thoughts, journal entries, or social media text to detect emotional patterns and assess mental health risk levels. By applying natural language processing and machine learning techniques, the system provides an effective approach for early mental health awareness and support.

The proposed system integrates text preprocessing, emotion analysis, and a trained machine learning model within a user-friendly web application to deliver real-time analysis results. In addition to prediction, the platform offers visual dashboards, emotion breakdowns, and personalized recommendations to help users understand their mental health condition. The system also supports result storage and advisor-level summaries, making it suitable for both individual use and guided mental health assessment. This project demonstrates how AI-based text analysis can provide a scalable, reliable, and accessible solution for mental health monitoring.

Keywords: Mental Health Analysis, Depression Detection, Natural Language Processing, Machine Learning, Emotion Analysis, Web Application.

Downloads: | DOI: 10.17148/IJARCCE.2026.151126