English

Forman curvature for complex networks

Molecular Networks 2016-06-23 v1 Disordered Systems and Neural Networks Physics and Society

Abstract

We adapt Forman's discretization of Ricci curvature to the case of undirected networks, both weighted and unweighted, and investigate the measure in a variety of model and real-world networks. We find that most nodes and edges in model and real networks have a negative curvature. Furthermore, the distribution of Forman curvature of nodes and edges is narrow in random and small-world networks, while the distribution is broad in scale-free and real-world networks. In most networks, Forman curvature is found to display significant negative correlation with degree and centrality measures. However, Forman curvature is uncorrelated with clustering coefficient in most networks. Importantly, we find that both model and real networks are vulnerable to targeted deletion of nodes with highly negative Forman curvature. Our results suggest that Forman curvature can be employed to gain novel insights on the organization of complex networks.

Keywords

Cite

@article{arxiv.1603.00386,
  title  = {Forman curvature for complex networks},
  author = {R. P. Sreejith and Karthikeyan Mohanraj and Jürgen Jost and Emil Saucan and Areejit Samal},
  journal= {arXiv preprint arXiv:1603.00386},
  year   = {2016}
}

Comments

18 pages, 15 figures. Supplementary material available upon request from authors

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