Abstract
As social media websites have emerged as popular platforms for sharing and spreading real-time information on the Internet, impostors see huge opportunities in taking advantage of such systems to spread distorted information. Online social networks and review websites have become targets of opinion spamming. More and more traditional review websites allow users to “friend” or “follow” each other so as to enhance overall user experience. This has brought significant advances of opinion spam detection using users’ social networks or heterogeneous networks of various entities in a broader sense. In this chapter, different techniques are introduced, such as belief propagation and collective positive-unlabeled learning, that leverage the intricate relations between different entities in the network. We discuss these methods via the application of spam detection on review-hosting websites and popular social media platforms.
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