Analyzing Tweets to Discover Twitter Users' Mental Health Status by a Word-Frequency Method

Mental Illness is reflected in the changes in isolation or combination of thinking, emotions, and expression of an individual. If an individual contemplates mental illness as any other medical problem, it is addressable within the medical science limits. However, the identification of mental illness in oneself is difficult, and normally, an individual does not accept to be a 'mental illness patient.' Social networks dominated in one's lifestyle, communication, expression, sharing the views, photos and voice, etc with the present technological advancement. Social Networks further connected people from far off places. Identification of Mental Health Status of an individual became important as his/her behavior is directly impact the social environment. There is a great advantage, if one can identify the Mental Health Status of an individual and find ways to measure it. We have attempted to identify the behavior of individuals through the tweets posted, and a relation between these illness and tweet words is established with our Word-Frequency method. Our analysis correlated well with the SVD method results.