Scale-free network growth by ranking

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dc.creatorFortunato, Santo
dc.creatorFlammini, Alessandro
dc.creatorMenczer, Filippo
dc.date2006-02-03
dc.date2006-05-09
dc.date.accessioned2026-07-07T07:37:18Z
dc.date.available2026-07-07T07:37:18Z
dc.descriptionNetwork growth is currently explained through mechanisms that rely on node prestige measures, such as degree or fitness. In many real networks those who create and connect nodes do not know the prestige values of existing nodes, but only their ranking by prestige. We propose a criterion of network growth that explicitly relies on the ranking of the nodes according to any prestige measure, be it topological or not. The resulting network has a scale-free degree distribution when the probability to link a target node is any power law function of its rank, even when one has only partial information of node ranks. Our criterion may explain the frequency and robustness of scale-free degree distributions in real networks, as illustrated by the special case of the Web graph.
dc.description4 pages, 2 figures. We extended the model to account for ranking by arbitrarily distributed fitness. Final version to appear on Physical Review Letters
dc.identifierhttps://arxiv.org/abs/cond-mat/0602081
dc.identifierhttp://arxiv.org/abs/cond-mat/0602081
dc.identifierPhys. Rev. Lett. 96, 218701 (2006)
dc.identifierdoi:10.1103/PhysRevLett.96.218701
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/120730
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.subjectPhysics and Society
dc.titleScale-free network growth by ranking
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