Local-Global Interaction and the Emergence of
Scale-Free Networks with Community Structures
Artificial Life, 17 (4):
263--279 (Jul 15, 2011)DOI: 10.1162/artl_a_00038
Abstract
Abstract Understanding complex networks in the real
world is a nontrivial task. In the study of community
structures we normally encounter several examples of
these networks, which makes any statistical inferencing
a challenging endeavor. Researchers resort to
computer-generated networks that resemble networks
encountered in the real world as a means to generate
many networks with different sizes, while maintaining
the real-world characteristics of interest. The
generation of networks that resemble the real world
turns out in itself to be a complex search problem. We
present a new rewiring algorithm for the generation of
networks with unique characteristics that combine the
scale-free effects and community structures encountered
in the real world. The algorithm is inspired by social
interactions in the real world, whereby people tend to
connect locally while occasionally they connect
globally. This local-global coupling turns out to be a
powerful characteristics that is required for our
proposed rewiring algorithm to generate networks with
community structures, power law distributions both in
degree and in community size, positive assortative
mixing by degree, and the rich-club phenomenon.
