Robustness of community structure in networks

by: Brian Karrer, Elizaveta Levina, MEJ Newman

Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), Vol. 77, No. 4. (2008)

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Abstract

The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated.

@article{karrer08, abstract = {The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated.}, author = {Karrer, Brian and Levina, Elizaveta and Newman, M. E. J. }, citeulike-article-id = {2748197}, doi = {http://dx.doi.org/10.1103/PhysRevE.77.046119}, journal = {Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)}, keywords = {modularity, network, robustness}, number = {4}, posted-at = {2008-05-03 14:17:01}, priority = {0}, publisher = {APS}, title = {Robustness of community structure in networks}, url = {http://dx.doi.org/10.1103/PhysRevE.77.046119}, volume = {77}, year = {2008} }

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TY - JOUR ID - karrer08 L3 - citeulike-article-id:2748197 TI - Robustness of community structure in networks JF - Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) VL - 77 IS - 4 PB - APS N2 - The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated. KW - modularity KW - network KW - robustness AU - Karrer, Brian AU - Levina, Elizaveta AU - Newman, MEJ PY - 2008/// UR - http://dx.doi.org/10.1103/PhysRevE.77.046119 ER -

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