A signature of power law network dynamics

Ashish Bhan; Animesh Ray

doi:10.1101/004028

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bioRxiv · 10.1101/004028

A signature of power law network dynamics

Ashish Bhan·Animesh Ray

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Abstract

Can one hear the sound of a growing network? We address the problem of recognizing the topology of evolving biological or social networks. Starting from percolation theory, we analytically prove a linear inverse relationship between two simple graph parameters--the logarithm of the average cluster size and logarithm of the ratio of the edges of the graph to the theoretically maximum number of edges for that graph--that holds for all growing power law graphs. The result establishes a novel property of evolving power-law networks in the asymptotic limit of network size. Numerical simulations as well as fitting to real-world citation co-authorship networks demonstrate that the result holds for networks of finite sizes, and provides a convenient measure of the extent to which an evolving family of networks belongs to the same power-law class.

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Ashish Bhan, Animesh Ray. 2014-04-09. A signature of power law network dynamics. https://doi.org/10.1101/004028

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