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arXiv 0709.2108physics.data-ancond-mat.stat-mechphysics.soc-ph
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Robustness of community structure in networks

Brian Karrer, Elizaveta Levina, M. E. J. Newman

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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