An information-theoretic framework for resolving community structure in complex networks Export

@article{citeulike:1270467, abstract = {10.1073/pnas.0611034104 To understand the structure of a large-scale biological, social, or technological network, it can be helpful to decompose the network into smaller subunits or modules. In this article, we develop an information-theoretic foundation for the concept of modularity in networks. We identify the modules of which the network is composed by finding an optimal compression of its topology, capitalizing on regularities in its structure. We explain the advantages of this approach and illustrate them by partitioning a number of real-world and model networks.}, author = {Rosvall, Martin and Bergstrom, Carl T.}, citeulike-article-id = {1270467}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0611034104}, citeulike-linkout-1 = {http://www.pnas.org/content/104/18/7327.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/104/18/7327.full.pdf}, citeulike-linkout-3 = {http://www.pnas.org/cgi/content/abstract/104/18/7327}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/17452639}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=17452639}, day = {1}, doi = {10.1073/pnas.0611034104}, journal = {Proceedings of the National Academy of Sciences}, keywords = {information-theory, networks, structure}, month = {May}, number = {18}, pages = {7327--7331}, posted-at = {2007-05-01 18:52:39}, priority = {2}, title = {An information-theoretic framework for resolving community structure in complex networks}, url = {http://dx.doi.org/10.1073/pnas.0611034104}, volume = {104}, year = {2007} }

TY - JOUR ID - citeulike:1270467 L3 - citeulike-article-id:1270467 N2 - 10.1073/pnas.0611034104 To understand the structure of a large-scale biological, social, or technological network, it can be helpful to decompose the network into smaller subunits or modules. In this article, we develop an information-theoretic foundation for the concept of modularity in networks. We identify the modules of which the network is composed by finding an optimal compression of its topology, capitalizing on regularities in its structure. We explain the advantages of this approach and illustrate them by partitioning a number of real-world and model networks. IS - 18 JF - Proceedings of the National Academy of Sciences EP - 7331 TI - An information-theoretic framework for resolving community structure in complex networks VL - 104 SP - 7327 KW - information-theory KW - networks KW - structure AU - Rosvall, Martin AU - Bergstrom, Carl PY - 2007/05/01/ UR - http://dx.doi.org/10.1073/pnas.0611034104 ER -