Mental Health Monitoring using Sentiment Analysis

Abstract

After a lot of research, there is no doubt in saying that overall physical, psychological and communal welfare of a human being is predominantly dependent on their mental health. Thus, early recognition and mediation in addressing issues regarding it should be our topmost priority. Individualized and ubiquitous sensing technologies such as smartphones, smartwatches, activity trackers, etc. allow continuous trackingand gathering of data in an undisturbed and low-profilemanner. Sentimental Analysis using Natural Language Processing has been proposed to be applied to the collected data to predict user information such as mood, activity, mental status, depression, anxiety, stress. The intent of this survey is to analyze and propose a methodology for data extraction and a model using Lambda Architecture to study the social media presence and other available data to predict the mental state of the user along with taking additional measures to maintain the secrecy of the user along with dataprivacy.