• Ankit Sahare
• Dr. Priyanka Dubey

The prevalence of stress-related mental health challenges in the digital era has prompted a surge in research focusing on automatic stress detection from online data. This paper presents a comprehensive framework for detecting stress using deep learning models applied to data extracted from social media platforms like Twitter and Reddit. Utilizing a combined dataset of over 5000 posts, the proposed pipeline integrates data preprocessing, exploratory data analysis, and classification using traditional machine learning models and BERT embeddings. Our results show promising performance in identifying stress-related content, offering significant implications for real-time mental health monitoring.

Stress Detection Mental Health Monitoring Social Media Analysis Deep Learning BERT Embeddings Natural Language Processing (NLP) Twitter and Reddit Online Behavioral Analysis Machine Learning Automatic Stress Classification

"Advanced Stress Detection Model Through Deep Learning In Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.h277-h285, May-2025, Available :http://www.jetir.org/papers/JETIR2505825.pdf

"Advanced Stress Detection Model Through Deep Learning In Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pph277-h285, May-2025, Available at : http://www.jetir.org/papers/JETIR2505825.pdf