Bipartite Graphs as Models of Complex Networks

By Jean-Loup Guillaume, Matthieu Latapy. Combinatorial and Algorithmic Aspects of Networking, 2003

343 citations recorded by the source corpus.

We propose here the first complex network model which achieves the following challenges: it produces graphs which have the three main wanted properties (clustering, degree distribution, average distance), it is based on some raal-world observations, and it is sufficiently simple to make it possible to prove its main properties. This model consists in sampling a random bipartite graph with prescribed degree distribution. Indeed, we show that any complex network can be viewed as a bipartite graph with some specific characteristics, and that its main properties can be viewed as consequences of this underlying structure.

Subfields: Geometry and Topology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/aee8b49f8f9d8daafce90c483228c2621d879a10

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geometry and Topology

In Statistical and Nonlinear Physics

Citations in the corpus

Complex network approaches to nonlinear time series analysis (2019, background): “Bipartite networks can be found in a wide range of fields [193,194] and can be understood as a generic way for describing arbitrary complex networks [195,196].”
Networks beyond pairwise interactions: structure and dynamics (2020, background): “[45] Jean-Loup Guillaume and Matthieu Latapy.”