Paper Title
Review on Social Media Data for Predicting Mental Health Illness

Abstract
Researchers have long been interested in determining the prevalence, causes, and prevention of depression, the most recent epidemic of the modern age. According to psychiatrists, it is not a psychological disorder, but it stimulates and simulates a lack of coordination. The increased usage of technology may result in a life style that involves less physical labour. Constant strain on an individual might also increase the likelihood of mental illness. Peer pressure, heart attacks, depression, and a variety of other factors are all potential risks.Thousands of millions of people suffer from depression each year, but only a small percentage obtain proper therapy. Depression is a genuine mental illness, which meddles most with the capacity to work, study, eat, rest and having a great time. In any case, from the client profile in Social media text, there is an assortment all the data that identifies with individual's state of mind, and negativism. To examine how Social media text client's posts can help arrange clients as per psychological wellness levels. This framework utilizes Social media text as a wellspring of information and screening apparatus to arrange the client utilizing man-made brainpower as indicated by the client post on Social organization using machine learning. Keywords - Mentall Illness, Machine Learning, Depression