Hasso Plattner Institut
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Ralf Krestel

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Using Co-occurence of Tags and Resources to identify Spammers

Today, more and more social networking websites support collaborative tagging, which allows users to annotate resources (e.g., video clips, blog posts, and bookmarks) on the web. Due to its increasing popularity, however, spammers started to target this new type of service and generate misleading tags either to increase the visibility of some resources or simply to confuse users. Consequently, the performance of applications built upon tag data, such as recovery and discovery of web resources, can be limited. In this paper, we propose an algorithm to identify spammers from the collaborating systems by employing a spam score propagating technique. The three dimensional relationship among users, tags and web resources is firstly represented by a graph structure. A set of seed nodes, where each node represents a user, are then selected and assigned values to indicate whether the corresponding users are spammers or not. The initial values are propagated through the graph to infer the status of the remaining users. Our experimental results demonstrate the effectiveness of this approach in identify tag spammers.
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