Detecting Communities from Social Tagging Networks Based on Tripartite Modularity

Online social media such as delicious and digg are represented as tripartite networks whose vertices are users, tags, and resources. Detecting communities from such tripartite networks is practically important. Newman-Girvan modularity is often used as the criteria for evaluating the goodness of network divisions into communities. Murata has extended Newman-Girvan modularity in order to evaluate the quality of the division of tripartite networks. This paper shows the results of community detection from large-scale real social tagging networks based on Murata’s tripartite modularity.

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