Ensembles based on the Rich-Club and how to use them to build soft-communities
arXiv:1504.05782
Abstract
Ensembles of networks are used as null-models to discriminate network structures. We present an efficient algorithm, based on the maximal entropy method to generate network ensembles defined by the degree sequence and the rich-club coefficient. The method is applicable for unweighted, undirected networks. The ensembles are used to generate correlated and uncorrelated null--models of a real networks. These ensembles can be used to define the partition of a network into soft communities.
arXiv comment16 pages, 5 figures
References in corpus (14)
- Finding and evaluating community structure in networks
- Community detection in graphs
- Finding community structure in networks using the eigenvectors of matrices
- Resolution limit in community detection
- Dynamical and correlation properties of the Internet
- Finding statistically significant communities in networks
- Detecting rich-club ordering in complex networks
- The Rich-Club Phenomenon In The Internet Topology
- Pattern Detection in Complex Networks: Correlation Profile of the Internet
- Robustness of community structure in networks
- The entropy of network ensembles
- Identifying "communities" within energy landscapes
- Randomizing world trade. I. A binary network analysis
- Randomizing world trade. II. A weighted network analysis