Taxonomy and clustering in collaborative systems: The case of the on-line encyclopedia Wikipedia (Articolo in rivista)

Type
Label
  • Taxonomy and clustering in collaborative systems: The case of the on-line encyclopedia Wikipedia (Articolo in rivista) (literal)
Anno
  • 2008-01-01T00:00:00+01:00 (literal)
Alternative label
  • Capocci, A; Rao, F; Caldarelli, G (2008)
    Taxonomy and clustering in collaborative systems: The case of the on-line encyclopedia Wikipedia
    in Europhysics letters (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Capocci, A; Rao, F; Caldarelli, G (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 81 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • \"[Capocci, A.] Univ Roma La Sapienza, Dipartimento Informat & Sistemist, I-00185 Rome, Italy; [Rao, F.; Caldarelli, G.] Ctr Ric & Museo Fis E Fermi, I-00185 Rome, Italy; [Caldarelli, G.] Univ Roma La Sapienza, Dipartimento Fis, INFM, CNR,SMC Ctr, I-00185 Rome, Italy; [Caldarelli, G.] Ctr Study Complex Networks, Linkalab, I-09100 Cagliari, Italy (literal)
Titolo
  • Taxonomy and clustering in collaborative systems: The case of the on-line encyclopedia Wikipedia (literal)
Abstract
  • In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia. We find a statistical similarity in the distributions of community sizes both by using the top-down approach of the categories division present in the archive and in the bottom-up procedure of community detection given by an algorithm based on the spectral properties of the graph. Regardless of the statistically similar behaviour, the two methods provide a rather different division of the articles, thereby signaling that the nature and presence of power laws is a general feature for these systems and cannot be used as a benchmark to evaluate the suitability of a clustering method. Copyright (C) EPLA, 2008. (literal)
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