Uncovering Hierarchical Structure in Social Networks Using Isospectral Reductions

We introduce a flexible method for determining the hierarchical structure of a network based on the theory of isospectral network reductions. To illustrate the usefulness of this approach we apply our procedure to the Southern Women Data Set, one of the most studied of all social networks. We find that these techniques provide new information that is consistent in a number of ways to previous results regarding this network but that is also complementary to these earlier findings.

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