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

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dc.creatorCosta, Luciano da F.
dc.creatorKaiser, Marcus
dc.creatorHilgetag, Claus
dc.date2006-07-29
dc.date.accessioned2026-07-07T07:22:46Z
dc.date.available2026-07-07T07:22:46Z
dc.descriptionDeviations 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.
dc.description1 figure, 1 table, 5 pages. A working manuscript. Comments very welcomed
dc.identifierhttps://arxiv.org/abs/physics/0607272
dc.identifierhttp://arxiv.org/abs/physics/0607272
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/115780
dc.subjectData Analysis, Statistics and Probability
dc.subjectDisordered Systems and Neural Networks
dc.subjectPhysics and Society
dc.titleBeyond the average: detecting global singular nodes from local features in complex networks
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