Emergence of Soft Communities from Geometric Preferential Attachment
arXiv:1501.06835 · doi:10.1038/srep09421
Abstract
All real networks are different, but many have some structural properties in common. There seems to be no consensus on what the most common properties are, but scale-free degree distributions, strong clustering, and community structure are frequently mentioned without question. Surprisingly, there exists no simple generative mechanism explaining all the three properties at once in growing networks. Here we show how latent network geometry coupled with preferential attachment of nodes to this geometry fills this gap. We call this mechanism geometric preferential attachment (GPA), and validate it against the Internet. GPA gives rise to soft communities that provide a different perspective on the community structure in networks. The connections between GPA and cosmological models, including inflation, are also discussed.
10 pages, 6 figures
References in corpus (9)
- Power-law distributions in empirical data
- Comparing community structure identification
- Sustaining the Internet with Hyperbolic Mapping
- Subnetwork hierarchies of biochemical pathways
- Triadic closure as a basic generating mechanism of communities in complex networks
- Network Cosmology
- Majority Model on a network with communities
- Preferential attachment of communities: the same principle, but a higher level
- Emergence of Clustering in an Acquaintance Model without Homophily
Cited by in corpus (7)
- Latent geometry of bipartite networks
- Gender and collaboration patterns in a temporal scientific authorship network
- Model-free hidden geometry of complex networks
- Geometric detection of hierarchical backbones in real networks
- Community detection in hypergraphs through hyperedge percolation
- Growing graphs with addition of communities
- Robustness and size-dependence of circadian rhythms in multiscale suprachiasmatic-nucleus networks