Accuracy and precision of methods for community identification in weighted networks |
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Authors: | Ying Fan Menghui Li Peng Zhang Jinshan Wu Zengru Di |
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Institution: | 1. Department of Systems Science, School of Management, Beijing Normal University, Beijing 100875, PR China;2. Department of Physics and Astronomy, University of British Columbia, Vancouver, B.C. Canada, V6T 1Z1 |
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Abstract: | Different algorithms, which take both links and link weights into account for the community structure of weighted networks, have been reported recently. Based on the measure of similarity among community structures introduced in our previous work, in this paper, accuracy and precision of three algorithms are investigated. Results show that Potts model based algorithm and weighted extremal optimization (WEO) algorithm work well on both dense or sparse weighted networks, while weighted Girvan–Newman (WGN) algorithm works well only for relatively sparse networks. |
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Keywords: | Weighted networks Community structure Similarity function |
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