  Complex networks of real-world systems are believed to be controlled by
common phenomena, producing structures far from regular or random. These
include scale-free degree distributions, small-world structure and assortative
mixing by degree, which are also the properties captured by different random
graph models proposed in the literature. However, many (non-social) real-world
networks are in fact disassortative by degree. Thus, we here propose a simple
evolving model that generates networks with most common properties of
real-world networks including degree disassortativity. Furthermore, the model
has a natural interpretation for citation networks with different practical
applications.
