Sentimental Analysis for Identifying Depression Level using Facebook Post

Abstract

Sentiment analysis is a method where the data is being analyzed may be a specific phrase, sentence, statement or a whole document to seek out different sentiments. Social media usage is increasing and gaining attention nowadays notably among the modern generation.  In demand of social media platforms and the rapidity with which they've  inserted themselves into nearly all facets of our lives, there's a exquisite loss of clear information approximately how they have an effect on us in my opinion: our behaviours, our societal relationships, and our intellectual health. The availability of Social Networking Site (SNS) like Facebook, allows users to convey their interests, feelings and share their day to day thoughts. Spending too much time on “social media like Facebook is making people more than just miserable. It may also be making them depressed. Several experimenter authenticate that using User-Generated Content (UGC) in an exceedingly correct approach might facilitate people's mental state levels Mining the UGC could help to guess the mental health levels and depression.  Depression could be a serious medical unwellness that interferes mostly with the power to study, eat, sleep and having fun. The information of a person's mood and negativism can be Gathered from the user profile in SNS, our aim is to analyse social networking site user's posts using sentimental analysis which will  classify users with mental state levels.