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ABSTRACT
Tagging systems allow users to interactively annotate a pool of shared resources using descriptive tags. As tagging systems are gaining in popularity, they become more susceptible to tag spam: misleading tags that are generated in order to increase the visibility of some resources or simply to confuse users. We introduce a framework for modeling tagging systems and user tagging behavior. We also describe a method for ranking documents matching a tag based on taggers' reliability. Using our framework, we study the behavior of existing approaches under malicious attacks and the impact of a moderator and our ranking method.
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CITED BY 17
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Michael G. Noll , Ching-man Au Yeung , Nicholas Gibbins , Christoph Meinel , Nigel Shadbolt, Telling experts from spammers: expertise ranking in folksonomies, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, July 19-23, 2009, Boston, MA, USA
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Fabrício Benevenuto , Tiago Rodrigues , Virgílio Almeida , Jussara Almeida , Marcos Gonçalves, Detecting spammers and content promoters in online video social networks, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, July 19-23, 2009, Boston, MA, USA
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