@misc{citeulike:155, abstract = {Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.}, author = {Newman, M. E. J.}, citeulike-article-id = {155}, eprint = {cond-mat/0303516}, interhash = {7bedd01cb4c06af9f5200b0fb3faa571}, intrahash = {d53568209eef08fb0a8734cf34c59a71}, keywords = {affinity algorithm arch clustering complex-systems folksonomy growth information_retrieval math network network_theory readinggroup scale-free-networks small_world socialnetwork systems thesis web web-graph}, month = {March}, priority = {5}, title = {The structure and function of complex networks}, url = {http://arxiv.org/abs/cond-mat/0303516}, year = 2003 }