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
%0 Journal Article
%1 citeulike:593564
%A Newman, M. E. J.
%D 2003
%J SIREV
%K research.conceptual.graphs science.statistics.powerlaw
%N 2
%P 167--256
%R 10.1137/S003614450342480
%T The Structure and Function of Complex Networks
%U http://epubs.siam.org/SIREV/volume-45/art_42480.html
%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{citeulike:593564,
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 = {2007-04-02T13:55:29.000+0200},
author = {Newman, M. E. J.},
biburl = {https://www.bibsonomy.org/bibtex/20d5909ac7bf3c5565bb204385a9f1661/msn},
citeulike-article-id = {593564},
doi = {10.1137/S003614450342480},
interhash = {7bedd01cb4c06af9f5200b0fb3faa571},
intrahash = {0d5909ac7bf3c5565bb204385a9f1661},
journal = {SIREV},
keywords = {research.conceptual.graphs science.statistics.powerlaw},
number = 2,
pages = {167--256},
priority = {3},
timestamp = {2007-04-02T13:55:29.000+0200},
title = {The Structure and Function of Complex Networks},
url = {http://epubs.siam.org/SIREV/volume-45/art_42480.html},
volume = 45,
year = 2003
}