Maps of random walks on complex networks reveal community structure
M. Rosvall, and C. Bergstrom. (2007)cite arxiv:0707.0609Comment: 7 pages and 4 figures plus supporting material. For associated source code, see http://www.tp.umu.se/~rosvall/.
DOI: 10.1073/pnas.0706851105
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.
Description
[0707.0609] Maps of random walks on complex networks reveal community structure
%0 Generic
%1 rosvall2007random
%A Rosvall, M.
%A Bergstrom, C. T.
%D 2007
%K compression encoding information networks paths theory walks
%R 10.1073/pnas.0706851105
%T Maps of random walks on complex networks reveal community structure
%U http://arxiv.org/abs/0707.0609
%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.
@misc{rosvall2007random,
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 = {2016-10-13T11:17:13.000+0200},
author = {Rosvall, M. and Bergstrom, C. T.},
biburl = {https://www.bibsonomy.org/bibtex/2c3f15307e50e3f080fb8a72e7c7fa5db/mbockholt},
description = {[0707.0609] Maps of random walks on complex networks reveal community structure},
doi = {10.1073/pnas.0706851105},
interhash = {73a98c601994f393a9c89ec25d9a5397},
intrahash = {c3f15307e50e3f080fb8a72e7c7fa5db},
keywords = {compression encoding information networks paths theory walks},
note = {cite arxiv:0707.0609Comment: 7 pages and 4 figures plus supporting material. For associated source code, see http://www.tp.umu.se/~rosvall/},
timestamp = {2016-10-13T11:17:13.000+0200},
title = {Maps of random walks on complex networks reveal community structure},
url = {http://arxiv.org/abs/0707.0609},
year = 2007
}