A network clustering method based on intersection of random spanning trees

We use a special edge centrality measure for node clustering in complex networks. The measure is based on the `spanning tree intersection' value motivated by previous work on the intersection and minimum expected overlap of random spanning trees in complex networks. First, we show that this new metric differs from some well-known edge centralities on random network models and real-world networks. Then, we show the applicability of the metric for clustering the nodes and point out some advantages over some other edge centrality based hierarchical clustering methods.

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Thematic Sessions: Short Papers