Fast extraction of the backbone of projected bipartite networks to aid community detection
RMIT University, School of Mathematical and Geospatial Sciences - Melbourne 3001, Australia
Received: 2 December 2015
Accepted: 25 January 2016
This paper introduces a computationally inexpensive method for extracting the backbone of one-mode networks projected from bipartite networks. We show that the edge weights in the one-mode projections are distributed according to a Poisson binomial distribution and that finding the expected weight distribution of a one-mode network projected from a random bipartite network only requires knowledge of the bipartite degree distributions. Being able to extract the backbone of a projection is highly beneficial in filtering out redundant information in large complex networks and narrowing down the information in the one-mode projection to the most relevant. We demonstrate that the backbone of a one-mode projection aids in the detection of communities.
PACS: 89.75.Hc – Networks and genealogical trees / 02.30.Mv – Approximations and expansions / 02.50.Ng – Distribution theory and Monte Carlo studies
© EPLA, 2016