Online Social Media Mining to Determine Mental Disorders in Social Network

Abstract

The growth in communication leads to heavy use of Social media. Due to this many personal disorders increases like online relationship addiction, information excess and online gambling have been lately identified. This disorders are difficult to identify manually because this issues are generally inactive. Due to development in technology there are many mining techniques available. These mining techniques are used to detect disordered patients at early stage.  We examine not only based on psychological but also to be specific interpersonal organizational mental confusion. This extracts features from social networks to find accurate potential cases. For improving the accuracy in social disorder uses the tensor based model. Our Structure is developed by examine study on many online social network users and this information is stored in datasets and analysed by dividing it into three social network mental disorder types.