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ROSARIO NUNZIO MANTEGNA

Core of communities in bipartite networks

  • Autori: Bongiorno, C.; London, A.; Micciche', S.; Mantegna, R.
  • Anno di pubblicazione: 2017
  • Tipologia: Articolo in rivista (Articolo in rivista)

Abstract

We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the coauthorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Rand index and the adjusted Wallace index, respectively. The detection of cores is highly precise, although the accuracy of the methodology can be limited in some cases.

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