%0 Journal Article %1 article:newman:2003 %A Newman, M. E. J. %D 2003 %J SIAM Review %K complex function graph networks structure theory to-read %N 2 %P 167-256 %T The Structure and Function of Complex Networks %U http://link.aip.org/link/?SIR/45/167/1 %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{article:newman:2003, 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 = {2008-11-17T12:27:50.000+0100}, author = {Newman, M. E. J.}, biburl = {https://www.bibsonomy.org/bibtex/2c7100a1c0f2c884343498b339a9fc3e0/mschuber}, interhash = {7bedd01cb4c06af9f5200b0fb3faa571}, intrahash = {c7100a1c0f2c884343498b339a9fc3e0}, journal = {SIAM Review}, keywords = {complex function graph networks structure theory to-read}, note = {publisher = {SIAM}, doi = {10.1137/S003614450342480}}, number = 2, pages = {167-256}, timestamp = {2008-11-17T12:28:12.000+0100}, title = {The Structure and Function of Complex Networks}, url = {http://link.aip.org/link/?SIR/45/167/1}, volume = 45, year = 2003 }