A Network Based Spam Detection Approach for Online Social Media Reviews Framework
Pages : 395-399
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Abstract
It depends on the content or opinion in social media to making a decision. For anytime, they choose to purchase or buying a product depending on the reviews and customer feedback. Possibility of writing a review gives a golden opportunity for spammers to put in writing spam reviews regarding the product and services for various demands and interests. Differentiate these spammers and the spam content could be an challenging issue of analysis. Though a fundamental range of studies are done towards this, the present date the technologies used now hardly search the spam reviews. Here, we are propose a new distinctive genuine platform called Net-Spam that uses spam options for modeling review data collection as diverse data networks to map spam detection procedure into classification. Mishandling the importance of spam options helps us to get best results in terms of different metrics experimented on real-world review data collection from Twitter and Amazon websites.
Keywords: Social Media, Mobile Apps, Social Network, Network Spammer, Spam Review and Rating, Ranking Fraud Detection, Evidence, Historical Records.