Mental Health Prediction Using Data Mining

Abstract

Mental illness is a condition that affects the behaviour, attitude and mannerisms of a person. They are highly common in these days of isolation due to the on-going pandemic. Almost 450 million people worldwide suffer from some kind of mental illness. Mental health problems do not only affect adults, but also it has significant impact on kids and teenagers. It is totally normal and understandable to experience fear during the time of COVID-19 pandemic. Loneliness, isolation, unhealthy alcohol and substance usage, self-harm or suicidal behaviour are all projected to escalate as new policies and impacts are implemented, especially quarantine and its effects on many people’s usual habits, schedules or livelihoods. Furthermore, psychiatric disorders have become one of the most severe and widespread public health issues. Early diagnosis of mental health issues is critical for further understanding mental health disorders and providing better medical care. Unlike the diagnosis of most health diseases, which is dependent on laboratory testing and measures, psychiatric disorders are usually classified based on a person’s self-report of detailed questionnaires intended to identify specific patterns. The project would use a person’s tweets, a few customized questions and answers, and a few personal data to measure a person’s mental well-being ranking. This initiative would be immensely helpful to anyone who uses social media sites on a regular basis in order to live a stress-free life and diagnose mental health problems before they get too serious.