Detection of Spam Messages in Social Networks based on SVM

Abstract

Social networks are platforms through which people communicate and share information. Some users commonly known as spammers are misusing these platforms for spreading unsolicited messages commonly known as spam messages. Due to the advancement of internet, it is very difficult to detect spam messages and fake profiles. This research article presents the use of a machine learning algorithm such SVM (Support Vector Machine), which is based on statistical learning methods to detect spam in social networks. This paper also evaluates the classification efficiency of Non Linear SVM using RBS (Radial Basis Function) Kernel.