Organization of Growing Random Networks
  The organizational development of growing random networks is investigated. These growing networks are built by adding nodes successively and linking each to an earlier node of degree k with attachment probability A_k. When A_k grows slower than linearly with k, the number of nodes with k links, N_k(t), decays faster than a power-law in k, while for A_k growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A_k is asymptotically linear, N_k(t) tk^{-nu}, with nu dependent on details of the attachment probability, but in the range 2<nu<infty. The combined age and degree distribution of nodes shows that old nodes typically have a large degree. There is also a significant correlation in the degrees of neighboring nodes, so that nodes of similar degree are more likely to be connected. The size distributions of the in-components and out-components of the network with respect to a given node -- namely, its "descendants" and "ancestors" -- are also determined. The in-component exhibits a robust s^{-2} power-law tail, where s is the component size. The out component has a typical size of order ln t and it provides basic insights about the genealogy of the network. 
P. L. Krapivsky and S. Redner