Information content: Assessing meso-scale structures in complex networks

Massimiliano Zanin, Pedro A Sousa, Ernestina Menasalvas

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

We propose a novel measure to assess the presence of meso-scale structures in complex networks. This measure is based on the identification of regular patterns in the adjacency matrix of the network, and on the calculation of the quantity of information lost when pairs of nodes are iteratively merged. We show how this measure is able to quantify several meso-scale structures, like the presence of modularity, bipartite and core-periphery configurations, or motifs. Results corresponding to a large set of real networks are used to validate its ability to detect non-trivial topological patterns.
Original languageEnglish
Article number30001
JournalEpl
Volume106
Issue number3
DOIs
Publication statusPublished - May 2014

Keywords

  • COMMUNITY STRUCTURE
  • SMALL-WORLD
  • BRAIN NETWORKS
  • SYNCHRONIZATION
  • DYNAMICS
  • SYSTEMS
  • MOTIFS

Fingerprint

Dive into the research topics of 'Information content: Assessing meso-scale structures in complex networks'. Together they form a unique fingerprint.

Cite this