AI in Mental Health: Sentiment Analysis and NLP for Early Detection of Depression and Anxiety

Abstract

Mental health disorders like depression and anxiety often go undiagnosed due to the stigma and lack of early detection mechanisms. This study presents an AI-based sentiment analysis framework utilizing Natural Language Processing (NLP) to analyze social media posts, therapy transcripts, and patient self-reports. Using deep learning models such as BERT and LSTMs, our system identifies linguistic patterns indicative of mental distress, providing an early warning system for mental health professionals. The results highlight AI’s potential to bridge the gap in mental health diagnostics and facilitate timely interventions.