Analysis of weighted networks Export

@article{citeulike:2201647, abstract = {The connections in many networks are not merely binary entities; either present or not; but have associated weights that record their strengths relative to one another. Recent studies of networks have; by and large; steered clear of such weighted networks; which are often perceived as being harder to analyze than their unweighted counterparts. Here we point out that weighted networks can in many cases be analyzed using a simple mapping from a weighted network to an unweighted multigraph; allowing us to apply standard techniques for unweighted graphs to weighted ones as well. We give a number of examples of the method; including an algorithm for detecting community structure in weighted networks and a simple proof of the maximum-flow–minimum-cut theorem.}, author = {Newman, M. E. J.}, citeulike-article-id = {2201647}, citeulike-linkout-0 = {http://dx.doi.org/10.1103/PhysRevE.70.056131}, citeulike-linkout-1 = {http://link.aps.org/abstract/PRE/v70/i5/e056131}, citeulike-linkout-2 = {http://link.aps.org/pdf/PRE/v70/i5/e056131}, day = {24}, doi = {10.1103/PhysRevE.70.056131}, journal = {Physical Review E}, keywords = {analysis, betweeness, complex\_network, wighted\_network}, month = {Nov}, number = {5}, pages = {056131+}, posted-at = {2009-08-06 01:58:55}, priority = {2}, publisher = {American Physical Society}, title = {Analysis of weighted networks}, url = {http://dx.doi.org/10.1103/PhysRevE.70.056131}, volume = {70}, year = {2004} }

TY - JOUR ID - citeulike:2201647 L3 - citeulike-article-id:2201647 N2 - The connections in many networks are not merely binary entities; either present or not; but have associated weights that record their strengths relative to one another. Recent studies of networks have; by and large; steered clear of such weighted networks; which are often perceived as being harder to analyze than their unweighted counterparts. Here we point out that weighted networks can in many cases be analyzed using a simple mapping from a weighted network to an unweighted multigraph; allowing us to apply standard techniques for unweighted graphs to weighted ones as well. We give a number of examples of the method; including an algorithm for detecting community structure in weighted networks and a simple proof of the maximum-flow–minimum-cut theorem. IS - 5 JF - Physical Review E TI - Analysis of weighted networks PB - American Physical Society VL - 70 SP - 056131 KW - analysis KW - betweeness KW - complex_network KW - wighted_network AU - Newman, MEJ PY - 2004/Nov/24/ UR - http://dx.doi.org/10.1103/PhysRevE.70.056131 ER -