Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media

People worldwide have suffered tremendously in terms of their mental health due to years of exposure to stress, anxiety, and the pressures of today's fast-paced lifestyles. The digitization of the data made possible by advances in health-care technology worldwide has allowed for a more precise mapping of the many variations of human biology than was possible before. People's methods of interaction with one another are evolving due to the rapid development of technology. Twitter, Facebook, Telegram, and Instagram have all risen to prominence as platforms where users can openly discuss their innermost thoughts, psyche, and feelings with one another. Texts are put through a psychological analysis process to pull out relevant details, characteristics, and user feedback. Psychological analysts rely on social media for the early identification of depressive symptoms and patterns of behavior. Machine learning has been recognized as a powerful method for sifting through the vast quantities of data in the health-care industry. Predicting the likelihood of mental diseases and executing likely treatment outcomes is a common application of ML techniques in mental health. This paper compiles a list of different mental health disorders along with the methods used in detecting and diagnosing mental health-related issues using online social media.