Spam detection using KNN and decision tree mechanism in social network

Social network (SN) is an online platform extensively used as communication tool by millions of society in order to built social relation with others for career purposes, knowledge point of view, politics and many more. In today's time everyone is online which make it today's most vast network of information. Different SN applications are available like Twitter, Facebook and MySpace through which peoples can communicate with other and send text, audio and video messages. During communication it is possible that a user can performs unwanted activities and send spam messages to disturb communication process. It is difficult to detect these kinds of spam messages. In this paper spam detection mechanism based on decision tree and KNN algorithm has been proposed. In proposed mechanism we apply these algorithms on real datasets of Twitter to detect spam messages. To analyse proposed mechanism Weka tool is used. The performance metrics like TP Rate, FP Rate, Precision, Recall, F-Measure and Class are used to measure the execution of proposed mechanism.