Internal links and pairs as a new tool for the analysis of bipartite complex networks

Oussama Allali, Lionel Tabourier, Clémence Magnien, Matthieu Latapy

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Abstract

Many real-world complex networks are best modeled as bipartite (or 2-mode) graphs, where nodes are divided into two sets with links connecting one side to the other. However, there is currently a lack of methods to analyze properly such graphs as most existing measures and methods are suited to classical graphs. A usual but limited approach consists in deriving 1-mode graphs (called projections) from the underlying bipartite structure, though it causes important loss of information and data storage issues. We introduce here internal links and pairs as a new notion useful for such analysis: it gives insights on the information lost by projecting the bipartite graph. We illustrate the relevance of theses concepts on several real-world instances illustrating how it enables to discriminate behaviors among various cases when we compare them to a benchmark of random networks. Then, we show that we can draw benefit from this concept for both modeling complex networks and storing them in a compact format.
Original languageEnglish
JournalSocial Network Analysis and Mining
Publication statusPublished - 22 Apr 2011

Keywords

  • cs.SI
  • physics.soc-ph

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