Abstract
Many real-world complex networks actually have a bipartite nature: their nodes may
be separated into two classes, the links being between nodes of different classes only.
Despite this, and despite the fact that many ad-hoc tools have been designed for the
study of special cases, very few exist to analyse (describe, extract relevant information)
such networks in a systematic way. We propose here an extension of the most basic
notions used nowadays to analyse classical complex networks to the bipartite case. To
achieve this, we introduce a set of simple statistics, which we discuss by comparing
their values on a representative set of real-world networks and on their random versions
Users
Please
log in to take part in the discussion (add own reviews or comments).