IDISORDER DETECTION USING MACHINE LEARNING

Abstract

Increased prevalence of social media usage across various age groups and social sectors and boom in popularity of cross media has led to the various muddles such as social network mental disorders (SNMDs) like Cyber-Relationship Addiction, Information Overload, and Net Compulsion etc. Based on a person’s usage pattern on social media, it is possible to predict of the person suffers from one of the 3 disorders mentioned above. In our project, we introduce a machine learning framework, namely Social Network Mental Disorder Detection (SNMDD) for mining online social behavior. It makes use of data sets extracted on browsing patterns to predict the presence of the 3 types of disorders mentioned above.