The purpose of this article is to illustrate, through the example of human dynamics, that a thorough understanding of complex systems requires an understanding of network dynamics as well as network topology and architecture. After an overview of the topology of complex networks, such as the Internet and the WWW, data-driven models for human dynamics are given. These models motivate the study of network dynamics and suggest that complexity theory must incorporate the interactions between dynamics and structure. The article also advances the notion that an understanding of network dynamics is facilitated by the availability of large data sets and analysis tools gained from the study of network structure.
%0 Journal Article
%1 Barabasi2007Architecture
%A Barabási, Albert-laszlo
%B Control Systems Magazine, IEEE
%D 2007
%J Control Systems Magazine, IEEE
%K review networks complexity
%N 4
%P 33--42
%R 10.1109/mcs.2007.384127
%T The Architecture of Complexity
%U http://dx.doi.org/10.1109/mcs.2007.384127
%V 27
%X The purpose of this article is to illustrate, through the example of human dynamics, that a thorough understanding of complex systems requires an understanding of network dynamics as well as network topology and architecture. After an overview of the topology of complex networks, such as the Internet and the WWW, data-driven models for human dynamics are given. These models motivate the study of network dynamics and suggest that complexity theory must incorporate the interactions between dynamics and structure. The article also advances the notion that an understanding of network dynamics is facilitated by the availability of large data sets and analysis tools gained from the study of network structure.
@article{Barabasi2007Architecture,
abstract = {{The purpose of this article is to illustrate, through the example of human dynamics, that a thorough understanding of complex systems requires an understanding of network dynamics as well as network topology and architecture. After an overview of the topology of complex networks, such as the Internet and the WWW, data-driven models for human dynamics are given. These models motivate the study of network dynamics and suggest that complexity theory must incorporate the interactions between dynamics and structure. The article also advances the notion that an understanding of network dynamics is facilitated by the availability of large data sets and analysis tools gained from the study of network structure.}},
added-at = {2019-06-10T14:53:09.000+0200},
author = {Barab\'{a}si, Albert-laszlo},
biburl = {https://www.bibsonomy.org/bibtex/2e45a3940a4949e85e26497c0057a2797/nonancourt},
booktitle = {Control Systems Magazine, IEEE},
citeulike-article-id = {5275125},
citeulike-linkout-0 = {http://dx.doi.org/10.1109/mcs.2007.384127},
citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=4272327},
doi = {10.1109/mcs.2007.384127},
interhash = {fbd91a79e806287ba0d78cf0469476d6},
intrahash = {e45a3940a4949e85e26497c0057a2797},
journal = {Control Systems Magazine, IEEE},
keywords = {review networks complexity},
number = 4,
pages = {33--42},
posted-at = {2009-07-26 22:58:48},
priority = {2},
timestamp = {2019-07-31T12:53:18.000+0200},
title = {{The Architecture of Complexity}},
url = {http://dx.doi.org/10.1109/mcs.2007.384127},
volume = 27,
year = 2007
}