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• W2011718069 abstract "A novel spectral approach for discovering community structure of undirected networks is introduced, using complex eigenvalues and eigenvectors of the Laplacian matrix of a directed network corresponding to the original undirected one. The effectiveness of the method depends on the type of directioning of the network. The role of directioning is discussed and it is shown that the best results are obtained for a balanced directioning in which the difference between in and out degrees of each node is at most 1. The method is tested by applying it to some computer-generated and real-world networks. Moreover, it is shown that for a network with hierarchical community structure, different topological scales can be revealed using different eigenvectors." @default.
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• W2011718069 date "2009-10-22" @default.
• W2011718069 modified "2023-10-17" @default.
• W2011718069 title "Complex eigenvectors of network matrices give better insight into the community structure" @default.
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• W2011718069 doi "https://doi.org/10.1088/1742-5468/2009/10/p10018" @default.
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