To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach that reveals
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.
%0 Journal Article
%1 Rosvall2007Maps
%A Rosvall, M.
%A Bergstrom, C. T.
%D 2007
%I National Academy of Sciences
%J Proceedings of the National Academy of Sciences
%K random\_walks networks clustering communities collaboration-networks
%N 4
%P 1118--1123
%R 10.1073/pnas.0706851105
%T Maps of random walks on complex networks reveal community structure
%U http://dx.doi.org/10.1073/pnas.0706851105
%V 105
%X To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach that reveals
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.
@article{Rosvall2007Maps,
abstract = {{To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach that reveals
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.}},
added-at = {2019-06-10T14:53:09.000+0200},
archiveprefix = {arXiv},
author = {Rosvall, M. and Bergstrom, C. T.},
biburl = {https://www.bibsonomy.org/bibtex/2d9d40c6dc8f72171e19ebe202174d166/nonancourt},
citeulike-article-id = {2283763},
citeulike-linkout-0 = {http://arxiv.org/abs/0707.0609},
citeulike-linkout-1 = {http://arxiv.org/pdf/0707.0609},
citeulike-linkout-2 = {http://dx.doi.org/10.1073/pnas.0706851105},
citeulike-linkout-3 = {http://www.pnas.org/content/105/4/1118.abstract},
citeulike-linkout-4 = {http://www.pnas.org/content/105/4/1118.full.pdf},
citeulike-linkout-5 = {http://www.pnas.org/cgi/content/abstract/105/4/1118},
citeulike-linkout-6 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2234100/},
citeulike-linkout-7 = {http://view.ncbi.nlm.nih.gov/pubmed/18216267},
citeulike-linkout-8 = {http://www.hubmed.org/display.cgi?uids=18216267},
day = 12,
doi = {10.1073/pnas.0706851105},
eprint = {0707.0609},
interhash = {73a98c601994f393a9c89ec25d9a5397},
intrahash = {d9d40c6dc8f72171e19ebe202174d166},
issn = {1091-6490},
journal = {Proceedings of the National Academy of Sciences},
keywords = {random\_walks networks clustering communities collaboration-networks},
month = nov,
number = 4,
pages = {1118--1123},
pmcid = {PMC2234100},
pmid = {18216267},
posted-at = {2009-10-07 11:40:32},
priority = {2},
publisher = {National Academy of Sciences},
timestamp = {2019-08-26T11:19:23.000+0200},
title = {{Maps of random walks on complex networks reveal community structure}},
url = {http://dx.doi.org/10.1073/pnas.0706851105},
volume = 105,
year = 2007
}