HMHDTML: Human Mental Health Detection Using Text and Machine Learning Model

Human mental health (HMH) is a serious chronic condition that affects how a person thinks, feels, and behaves negatively. It is a common but serious mood disorder. About 20% of women will experience at least one episode of depression across their lifetime. Scientists examining many potential causes for and contributing factors to women’s increased risk for depression. To diagnose depression, the symptoms must be present at least 2 weeks. A research study has been conducted by detection of depression using sentiment analysis on Twitter, Facebook, Instagram, etc., to understand their behavioral symptoms like depressed mood, loss of interest, change in sleeping, difficulty in thinking and/or concentrating, taking decisions. This paper describes the features and the implementation of the depression using Twitter and sarcastic text with the help of machine learning algorithm to improve the overall results.