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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Detecting Hierarchical Organization in Complex Networks by Nearest Neighbor Correlation
verfasst von : Chao Long Wang, Ka Wai Au, Ching King Chan, Hon Wai Lau, K. Y. Szeto
Erschienen in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
Verlag: Springer Berlin Heidelberg
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The hierarchical organization in complex networks is investigated from the point of view of nearest neighbor correlation. By plotting the mean total degree of the nearest neighbors versus degree of the given node, more than one linear branches will be observed for hierarchical network. An example of hierarchical network with 1-hub-4-peripheral is constructed for illustrative purpose and real data on the World Wide Web and AS Internet are analyzed for comparison. Two branches are clearly observed for the total degree of neighbors of the World Wide Web, indicative of the existence of hierarchical organization and the result is consistent with the analysis based on local clustering coefficient. Only one branch is observed for the AS Internet data set, but the result is not conclusive as the size of the data set is not sufficiently large. The total degree of nearest neighbor provides a good complementary test to the existing method based on the local clustering coefficients.