Machine Learning For Prediction Of Malicious Or SPAM Users On Social Networks
The use of social networking is very much prevalent now a days as a part of an individual for interaction with friends and family. The reason of such development is the limited time and greater geographical distances between the net users. Further it provide the easy mean for interacting. But at the same time the social interaction platforms are very much at the target of spammers and content polluters. In this regards it is very high time for researchers to explore and provide the necessary framework for monitoring and identifying such individuals and bots which are based on machine learning approach. A manual way of identifications using human intervention is definitely a very time consuming and rigorous process. In this paper a provisioning of machine learning based approach based on artificial neural networks usage in determined for identifications of such bots or individuals. Various types of neural networks and tier relative outcomes are compared and evaluated for spam identification in this paper.