Systematic evaluation of a new combinatorial curvature for complex networks
R.P. Sreejith, Jürgen Jost, Emil Saucan, and Areejit Samal
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Submission date: 07. Oct. 2016 (revised version: May 2017)
published in: Chaos, solitons and fractals, 101 (2017), p. 50-67
DOI number (of the published article): 10.1016/j.chaos.2017.05.021
MSC-Numbers: 05C82, 05C7
Keywords and phrases: complex networks, Edge-based measures, Forman curvature
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We have recently introduced Forman’s discretization of Ricci curvature to the realm of complex networks. Forman curvature is an edge-based measure whose mathematical definition elegantly encapsulates the weights of nodes and edges in a complex network. In this contribution, we perform a comparative analysis of Forman curvature with other edge-based measures such as edge betweenness, embeddedness and dispersion in diverse model and real networks. We find that Forman curvature in comparison to embeddedness or dispersion is a better indicator of the importance of an edge for the large-scale connectivity of complex networks. Based on the definition of the Forman curvature of edges, there are two natural ways to define the Forman curvature of nodes in a network. In this contribution, we also examine these two possible definitions of Forman curvature of nodes in diverse model and real networks. Based on our empirical analysis, we find that in practice the unnormalized definition of the Forman curvature of nodes with the choice of combinatorial node weights is a better indicator of the importance of nodes in complex networks.