Growing scale-free networks with small-world behavior -: art. no. 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 logarithmically as in random networks, the clustering coefficient assumes a large value independent of system size. We derive analytical expressions for the clustering coefficient in two limiting cases: random [C similar to (In N)(2)/N] and highly clustered (C = 5/6) scale-free networks.