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We present a new method for decomposing a social network into an optimal number of hierarchical subgroups. With a perfect hierarchical subgroup defined as one in which every member is automorphically equivalent to each other, the method uses the REGGE algorithm to measure the similarities among nodes and applies the k-means method to group the nodes that have congruent profiles of dissimilarities...
We present an algorithm for decomposing a social network into an optimal number of structurally equivalent classes. The k-means method is used to determine the best decomposition of the social network for various numbers of subgroups. The best number of subgroups into which to decompose a network is determined by minimizing the intra-cluster variance of similarity subject to the constraint that the...
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