Beyond the average: detecting global singular nodes from local features in complex networks

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Deviations from the average can provide valuable insights about the organization of natural systems. This article extends this important principle to the more systematic identification and analysis of singular local connectivity patterns in complex networks. Four measurements quantifying different and complementary features of the connectivity around each node are calculated and multivariate statistical methods are then applied in order to identify outliers. The potential of the presented concepts and methodology is illustrated with respect to a word association network.
1 figure, 1 table, 5 pages. A working manuscript. Comments very welcomed

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Data Analysis, Statistics and Probability, Disordered Systems and Neural Networks, Physics and Society

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http://salesiana.dossiersoluciones.com/handle/123456789/115780

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/physics/0607272
 http://arxiv.org/abs/physics/0607272

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arXiv