Message Classification and Filtration from Social Networking Platforms Using Radial Basis Neural Network Classifier

Online Social networking (OSN) platforms are being used today very commonly. These Online social networking sites allow their users to post messages or write comments on an area called as the user wall. However these OSNs provide very little control to the users on the content of messages being posted on their walls. In this paper, the proposed system gives the user the ability to control the content of messages being posted. The messages are classified into different categories such as Sexual, Political, Religious and Vulgar. Based on the output of the classification, the filtering rules decide the posting of messages on the user walls. The classification is done using two different classifiers, Radial Basis Probabilistic Neural network and Radial Basis Function Network. The comparative performance study shows the effectiveness of the Radial Basis Probabilistic Neural Network classification technique and is able to produce more accurate results as compared to the latter classifier. The proposed system also gives recommendations of filtering rules to the users using collaborative filtering technique.