Psychological stress poses a significant A hazard to public health, necessitating timely detection for proactive care. The widespread use of social media provides an opportunity utilizing data from online social networks for stress identification.The study investigates, examines the relationship between individuals' stress levels and their social interactions through analysis of a vast data set obtained from real-world social platforms.By analyzing characteristics associated with stress encompassing textual, visual, and social aspects. we propose a novel approach for stress identification.Experimental findings showcase that our model enhances detection performance significantly. Additionally, we have developed a user-friendly website enabling individuals To evaluate their stress levels and investigate associated activities facilitating proactive stress management. Our aim to enhance stress identification by utilizing the dynamics of online social networks interactions. This study explores the intricate relationship the association between users' stress levels and their social networks. on various online platforms. By defining a A comprehensive array of stress-related features encompassing textual, visual, and social dimensions. we introduce a robust model for stress detection. Our experimental findings underscore the efficiency of this model in enhancing the accuracy of stress detection.