Social Interactions for Detecting Stress Based Issues

Abstract

Mental stress is showing harmfulness to human health leads abnormal stress in chronology with this may lose our mental health for proactive care. With recognizable pieces of proof of web-based media, individuals cannot share their everyday exercises and collaborate with companions via web-based media stages, making it happing to use online informal community information for stress identification. We find that users stress state is closely associated with thereupon of his/her friends in social media, which we employ a large-scale dataset from real-world social platforms to systematically study the relationship between users’ stress states and social interactions. We first define a gaggle of stress-related comments, images, and social attributes from various aspects, then proposed a plot. Research results saying that the proposed model can improve the detection performance. With the help of enumeration, we build an internet site for the users to spot their stress rate level and may check other related activities.