Abstract— In the present generation, the social life of everyone has becomeassociated with the online social networks. These sites have made a drasticchange in the way we pursue our social life. Making friends and keeping incontact with them and their updates has become easier. But with their rapidgrowth, many problems like fake profiles, online impersonation have also grown.There are no feasible solution exist to control these problems. In this project,we came up with a framework with which automatic detection of fake profiles ispossible and is efficient. This framework uses classification techniques likeSupport Vector Machine, Nave Bayes and Decision trees to classify the profilesinto fake or genuine classes. As, this is an automatic detection method, it canbe applied easily by online social networks which has millions of profile whoseprofiles cannot be examined manually.
Keywords: Item reputation, Reviews,Rating prediction, Recommender system, Sentiment influence, User sentiment.