DEPRESSION DETECTION USING MACHINE LEARNING

DEPRESSION DETECTION USING MACHINE LEARNING

Udit Mohanty, Pratyasha Samal

Abstract- Internet is considered as a major storehouse of information in today’s world. No single work can be done without help. It has become one of the major ways of communication. Out of all communication methods available, social media is one of the most common forms. Social media has changed the world. The number of internet users worldwide in 2019 is 4.388 billion, up 9.1% year-on-year. The number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year. People have a need to fit in to be visible praised in this new digital world. Social Media has many ill effects such as Cyber-bullying, Harassment and Depression. It is an almost undisputable truth that access to a cloak of anonymity and a large, large microphone brings the worst out in some people. Today, this is particularly true on social media. Online harassment and hate- messaging is a growing trend and a growing security concern for anyone on social media today. In fact, 40% of Internet users say they have personally experienced online harassment. Researchers have found that the longer you spend on social media, the more likely you are to be depressed. Hence, we have come up with this project in which we will be developing a system that helps in detecting a depressive and harassment text.

Keywords- Online harassment, Depression, Cyber-bullying, social media, Internet