Netspam: An Efficient Approach to Prevent Spam Messages using Support Vector Machine IJTSRD


The most common mode for consumers to express their level of satisfaction with their purchases is through online ratings, which we can refer as Online Review System. Network analysis has recently gained a lot of attention because of the arrival and increasing attractiveness of social sites, such as blogs, social networks, micro blogging, or customer review sites. The reviews are used by potential customers to find opinions of existing users before purchasing the products. Online review systems play an important part in affecting consumers’ actions and decision making, and therefore attracting many spammers to insert fake feedback or reviews to manipulate review content and ratings. Malicious users misuse the review website and post untrustworthy, low quality, or sometimes fake opinions, which are referred as Spam Reviews. In this study, we aim at classifying reviews as positive, negative and spam reviews by creating a social network similar platform and providing communication between users in it.

By P. Sai Kiran | K. Prudhvi Chowdary | T. T. Venkata Rayudu | K. Vinay Kumar”Netspam: An Efficient Approach to Prevent Spam Messages using Support Vector Machine”

Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018,

URL: http://www.ijtsrd.com/papers/ijtsrd11419.pdf

http://www.ijtsrd.com/computer-science/computer-network/11419/netspam-an-efficient-approach-to-prevent-spam-messages-using-support-vector-machine/p-sai-kiran

call for paper Artificial Intelligence, international journal Bioinformatics, ugc approved journals Cognitive Science




Netspam: An Efficient Approach to Prevent Spam Messages using Support Vector Machine IJTSRD IEEE PAPER





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