Mental Health Monitoring Using Sentimental Analysis

Abstract

Mental health is an indicator of psychological, social and emotional well- being of an individual. Almost all parts of society is affected by the underlying and unnoticed mental disorders. Popular social networking websites can play a major role in detecting these dangerous psychological patterns. The sequence of mental disorders around the globe can show the thoughts and felling of individuals . According to recent studies and the reports of WHO, almost 70% of world’s population is suffering from some kind of mental disorder and it sums upto a remarkable number. Health systems however have not responded adequately to burden of mental disorder. More than half of the population doesn’t have proper knowledge of the topic and those who know do not have a proper system to deal with it. A lot of enhancement in health care system is the need of time along with better awareness programs .People with mental health illness require adequate knowledge, social support and care.

This paper targets twitter as a platform to find the pattern of mental  illnesses.     Sentiment     analysis     method     is   used   to    find different behavioral patterns in diverse classification of mental disorders . To tackle the growing problem we present a new approach by focusing on the analysis of various disorders by using the respective hash tags on twitter. Neural network algorithms like CNN and front end application to depict the output is proposed using react as front end with REST APIframework.