Volume 113, Number 2, January 2016
|Number of page(s)||6|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||11 February 2016|
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
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.