We survey and synthesize models of network formation based on random graphs and stochastic processes. We organize the material according to whether the population is treated as fixed or dynamic. We pay particular attention to the effects of homophilous linking on network structure. Finally, we...

We present a new approach to the study of networks where the formation of links is driven by unilateral initiative of nodes. First, we propose a mathematical description of the extreme introvert and extrovert model (XIE), a dynamic network model in which the number of links fluctuates over time...

Random graph generation is an important tool for studying large complex networks. Despite abundance of random graph models, constructing models with application-driven constraints is poorly understood. In order to advance state-of-the-art in this area, we focus on random graphs without short...