Mental Health Analysis on Twitter Data

The rise in mental health disorders is a major issue that is being witnessed by all of us daily. According to the World Health Organization (WHO), people with severe mental disorders die 10 to 20 years earlier than the general population. PTSD, anxiety, depression, etc. are some of the common mental disorders which affect people and lead to severe outcomes. Social media has served as a major platform for millions of people to speak and share their experiences. It provides mass communication which promotes awareness among people and even gets advice from each other in a safe space. One of the major issues is that people do not even recognize the type of disorder they are going through, so they end up getting no proper diagnosis for it. Artificial intelligence (AI) methods have been proven very beneficial to understand these disorders and their effect on society. In this paper, we are providing work on mental health analysis which we performed on Twitter data. We have focused on these five mental disorders for classification: depression, anxiety, PTSD, bipolar, and eating disorder. We used machine learning and deep learning methods to perform classification and analyzed the tweets to get insights on the mentioned disorders. This study can help to understand these disorders more deeply and provide valuable insights to professionals for providing suitable treatment.