%0 Generic %1 Newman2003 %A Newman, M. E. J. %D 2003 %K complex-network structure %T The structure and function of complex networks %U http://arxiv.org/abs/cond-mat/0303516 %X 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.

@misc{Newman2003, 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. }, added-at = {2009-02-26T11:39:12.000+0100}, author = {Newman, M. E. J.}, biburl = {https://www.bibsonomy.org/bibtex/2d53568209eef08fb0a8734cf34c59a71/anneba}, description = {The structure and function of complex networks}, interhash = {7bedd01cb4c06af9f5200b0fb3faa571}, intrahash = {d53568209eef08fb0a8734cf34c59a71}, keywords = {complex-network structure}, note = {cite arxiv:cond-mat/0303516 Comment: Review article, 58 pages, 16 figures, 3 tables, 429 references, published in SIAM Review (2003)}, timestamp = {2009-02-26T11:39:12.000+0100}, title = {The structure and function of complex networks}, url = {http://arxiv.org/abs/cond-mat/0303516}, year = 2003 }