Growing Scale-Free Networks with Small World Behavior

Physics – Condensed Matter

Scientific paper

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4 pages, 4 figures

Scientific paper

10.1103/PhysRevE.65.057102

In the context of growing networks, we introduce a simple dynamical model that unifies the generic features of real networks: scale-free distribution of degree and the small world effect. While the average shortest path length increases logartihmically as in random networks, the clustering coefficient assumes a large value independent of system size. We derive expressions for the clustering coefficient in two limiting cases: random (C ~ (ln N)^2 / N) and highly clustered (C = 5/6) scale-free networks.

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