Deep Learning Based Model for Stress Measurement in Online Social Networks

Online Social Networks (OSNs) have become ubiquitous platforms for individuals to express their thoughts and emotions, making them valuable sources for studying mental health. This paper presents a novel Deep Learning-based approach for stress measurement in OSNs. We leverage a comprehensive dataset collected from Kaggle, specifically curated for stress analysis in social media. The proposed model demonstrates remarkable accuracy in identifying stress levels, paving the way for proactive mental health interventions and more targeted support systems in the digital age. This research contributes to the growing body of knowledge addressing mental health challenges in the online world, emphasizing the potential of AI and deep learning techniques in this critical domain.