Detection of Unwanted Messages and Fraudulent User Identification on Social Network

Abstract

Nowadays, social networking sites play a vital role for users to communicate and sharing information with other users online. Statistical analysis show that, on average, people spend most of their time on Facebook and Twitter which are constantly maintaining their position in most-viewed social networking sites than other sites. Usually many social networking users share their personal information and interest to other users publically. This leads to violation of privacy and attracts many intruders to steal their personal information and use them in an unauthorized manner. So there emerges a major concern in securing their personal details from fake ids and cyber security has become very crucial. In this paper, spammer identification technique on social networks like Facebook,Twitter are addressed. It has been implemented based on URL used by the user, trending topics and fake content shared by the users and fake users.  Various   kinds of features which are posted by the users are identified from which the nature of the user is detected as spam or not. Statistical studies proved that, this spammer detection schemes improves the detection accuracy rate constantly