Structural patterns in complex networks through spectral analysis

  • Authors:
  • Ernesto Estrada

  • Affiliations:
  • Department of Mathematics and Statistics, Department of Physics and Institute of Complex Systems, University of Strathclyde, Glasgow

  • Venue:
  • SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
  • Year:
  • 2010

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Abstract

The study of some structural properties of networks is introduced from a graph spectral perspective. First, subgraph centrality of nodes is defined and used to classify essential proteins in a proteomic map. This index is then used to produce a method that allows the identification of superhomogeneous networks. At the same time this method classify non-homogeneous network into three universal classes of structure. We give examples of these classes from networks in different real-world scenarios. Finally, a communicability function is studied and showed as an alternative for defining communities in complex networks. Using this approach a community is unambiguously defined and an algorithm for its identification is proposed and exemplified in a real-world network.