%0 Journal Article %1 newman2003structure %A Newman, M.E.J. %D 2003 %I JSTOR %J SIAM review %K %N 2 %P 167--256 %R 10.1137/S003614450342480 %T The Structure and Function of Complex Networks %V 45 %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.

@article{newman2003structure, 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 = {2011-12-08T08:38:58.000+0100}, author = {Newman, M.E.J.}, biburl = {https://www.bibsonomy.org/bibtex/2cf461fed5e29f83bd9f3726a1713a832/folke}, doi = {10.1137/S003614450342480}, interhash = {7bedd01cb4c06af9f5200b0fb3faa571}, intrahash = {cf461fed5e29f83bd9f3726a1713a832}, issn = {0036-1445}, journal = {SIAM review}, keywords = {}, number = 2, pages = {167--256}, publisher = {JSTOR}, timestamp = {2011-12-08T08:38:58.000+0100}, title = {The Structure and Function of Complex Networks}, volume = 45, year = 2003 }