Paper Contents
Abstract
Mental health such as depression, anxiety, and stress affects millions of individuals worldwide. While many suffer in silence, people increasingly share their emotions and mental stats on social media platforms like Twitter and Reddit. These digital expressions, often unfiltered and spontaneous, can offer critical insight into a person's psychological well-being. This research project explores how Natural Language Processing (NLP) can be used to analyse social media text to detect early signs reprocessing publicly available English language posts from social media, the study aims to identify linguistic patterns and emotional cues that indicate mental health conditions. Machine learning and Deep learning model including logistic regression, support vector machine (SVM) random forest and LSTM network-will be applied to develop a system capable of predicting potential mental health issue based on a language use. The goal is not to replace professional diagnosis but create a supportive tool for early detection and introversion. The project emphasizes ethical consideration ensuring by privacy, using only publicly available data, and focusing on responsible AI practices the anticipated outcome is scalable and ethical solution that leverages digital footprints to support mental health awareness and proactive care in todays increasingly online society.
Copyright
Copyright © 2025 Vishakha Jadhav. This is an open access article distributed under the Creative Commons Attribution License.
