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 Generic
%1 newman2003structure
%A Newman, M. E. J.
%D 2003
%K folksonomy_socialnetwork information small_world diploma_thesis complex_systems eventually_useful web_graph scale_free_networks clustering
%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{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 = {2011-01-28T11:34:48.000+0100},
author = {Newman, M. E. J.},
biburl = {https://www.bibsonomy.org/bibtex/2d53568209eef08fb0a8734cf34c59a71/dbenz},
file = {newman2003structure.pdf:newman2003structure.pdf:PDF},
interhash = {7bedd01cb4c06af9f5200b0fb3faa571},
intrahash = {d53568209eef08fb0a8734cf34c59a71},
keywords = {folksonomy_socialnetwork information small_world diploma_thesis complex_systems eventually_useful web_graph scale_free_networks clustering},
lastdatemodified = {2006-10-07},
lastname = {Newman},
month = {March},
own = {notown},
pdf = {newman03-structure.pdf},
read = {notread},
timestamp = {2013-07-31T15:39:42.000+0200},
title = {The structure and function of complex networks},
url = {http://arxiv.org/abs/cond-mat/0303516},
year = 2003
}