Detecting online social network addiction among users

With the increased number of online social networks (OSNs), the problems associated with excessive use and addiction to Social Medias has become more and more epidemic. This kind of addiction has negative impact on real user’s life, since developing a method to addict detection is essentially. In this paper user addiction is considered as abnormal behavior. We proposed an approach to detect addiction among Iranian Instagram users, initially, the Bergen social network addiction scale (BSMAS) based questionnaire was designed and then we asked Instagram users to fill that, secondary we collected profile and activity data from respondents pages, then some classification algorithm is used for classify users as addict or non-addict. Then we measure accuarcy of these classifiers and evalute theier performance with some measures.

کلیدواژه ها:

Online social network ، Classification ، Addiction