Random Networks with Tunable Degree Distribution and Clustering

Details Random Networks with Tunable Degree Distribution and Clustering Random Networks with Tunable Degree Distribution and Clustering

2004-05-17

arxiv.org/abs/cond-mat/0405381v2

Physics

Condensed Matter

Statistical Mechanics

9 pages, 13 figures corrected typos, added two references, reorganized references

Scientific paper

10.1103/PhysRevE.70.056115

We present an algorithm for generating random networks with arbitrary degree distribution and Clustering (frequency of triadic closure). We use this algorithm to generate networks with exponential, power law, and poisson degree distributions with variable levels of clustering. Such networks may be used as models of social networks and as a testable null hypothesis about network structure. Finally, we explore the effects of clustering on the point of the phase transition where a giant component forms in a random network, and on the size of the giant component. Some analysis of these effects is presented.

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