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

Oussama Allali 1 Lionel Tabourier 1 Clémence Magnien 1 Matthieu Latapy 1
1 ComplexNetworks
LIP6 - Laboratoire d'Informatique de Paris 6
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 a bipartite analysis, which gives insights into the information lost by projecting the bipartite graph. We illustrate the relevance of these concepts in several real-world instances, illustrating how it enables to discriminate behaviors among various cases when we compare them to a benchmark of random graphs. Then, we show that we can draw benefit from this concept for both modeling complex networks and storing them in a compact format.
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Submitted on : Monday, April 27, 2015 - 4:01:05 PM
Last modification on : Friday, January 8, 2021 - 5:32:05 PM

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Oussama Allali, Lionel Tabourier, Clémence Magnien, Matthieu Latapy. Internal links and pairs as a new tool for the analysis of bipartite complex networks. Social Network Analysis and Mining, Springer, 2013, 3 (1), pp.85-91. ⟨10.1007/s13278-012-0053-0⟩. ⟨hal-01146082⟩



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