• Miss. Shrusti B. Kharde
• Prof. Anuradha. N. Nawathe

In online world, for expressing opinions and interacting with other people Social networks are a very popular way. We know that every good things have some part of bad thing that effects on human life. So we are trying to saves human life from social addiction. Social addicted persons are identifies by using Support Vector Machine Algorithm by classifying in stress or non-stress class. Also to improve our system goal, we further create a mobile app that give user’s monthly activities perform on application in mobile and suggest such user about their usage to prevent from social addiction. Here we are trying to prevent user from unnecessary usages of application.

Support Vector Machine, mental disorder, social network, classification.

"Detecting Mental Disorder on Social Interactions in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.463-467, June-2019, Available :http://www.jetir.org/papers/JETIR1906B74.pdf

"Detecting Mental Disorder on Social Interactions in Social Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp463-467, June-2019, Available at : http://www.jetir.org/papers/JETIR1906B74.pdf