• Snehal B. Shelke
• Priyanka N. Kokare

: In the recent years Psychological stress is enhancing risk to people’s health. The growth of online social media platform, so that several public are feeling stressed as well as it is not easy to detect users stress states in an previous stage to secure user also popularity of social media, people are used to share their daily activities and connecting with friends on social media sites like Facebook, twitter Sina Weibo2 etc. This paper described the detail survey of stress detection system which is based on social media platform. This system developed the framework to detect users psychological stress states. It is exactly relevant to user’s friends in social media and provides an extensive dataset from real-world social platforms to methodically survey of interconnection of users stress states and social interactions. In this system initially determine a cluster of stress which is relevant to textual, visual, and social attributes. Afterwards convolutional neural network which is used for topic extraction. It performs sentiment analysis of Facebook post after formation of topic. The contribution task is detecting users stress states by using support vector machines, after classification of users are in stress or not, then K-nearest neighbors algorithm is used for recommendation of hospital on a map as well as send mail of precaution list to user for become healthy and happy in life.

Factor Graph Model, Healthcare, Support Vector Method

"Stress Detection System on Social Interactions In Social Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.86-89, May-2019, Available :http://www.jetir.org/papers/JETIRBO06013.pdf

"Stress Detection System on Social Interactions In Social Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp86-89, May-2019, Available at : http://www.jetir.org/papers/JETIRBO06013.pdf