Clustering coefficient without degree correlations biases

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dc.creatorSoffer, Sara Nadiv
dc.creatorVazquez, Alexei
dc.date2004-09-26
dc.date.accessioned2026-07-07T03:01:02Z
dc.date.available2026-07-07T03:01:02Z
dc.descriptionThe clustering coefficient quantifies how well connected are the neighbors of a vertex in a graph. In real networks it decreases with the vertex degree, which has been taken as a signature of the network hierarchical structure. Here we show that this signature of hierarchical structure is a consequence of degree correlation biases in the clustering coefficient definition. We introduce a new definition in which the degree correlation biases are filtered out, and provide evidence that in real networks the clustering coefficient is constant or decays logarithmically with vertex degree.
dc.description4 pages, 3 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0409686
dc.identifierhttp://arxiv.org/abs/cond-mat/0409686
dc.identifierPhys. Rev 71, 057101 (2005)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/24941
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titleClustering coefficient without degree correlations biases
dc.typetext

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