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The similarity of weights on edges and discovering of community structure

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  • Shen, Yi

Abstract

In this paper, we propose a weighted modularity QW based on the similarity of weights on edges and a threshold coefficient ζ to evaluate the equivalence of edge weights. Simulations on benchmark networks and real networks show that optimization on the modularity enable us to obtain groups of nodes within which the edge weights are distributed uniformly but at random between them. The communities can reveal the uniform connections (stable relationships measured by the similarity of weights on edges) between nodes or some similarity between nodes’ functions. Furthermore, with the dynamical moving of ζ, we observe that optimization on the QW allows for the discovering of a special hierarchical organization which reveals different levels of uniform connections between nodes in networks. The substructures revealed by the hierarchical organization enable us to obtain more information of networks, and give a potential way for partly remedying the intrinsic resolution problem of modularity.

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  • Shen, Yi, 2014. "The similarity of weights on edges and discovering of community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 560-570.
    • Handle: RePEc:eee:phsmap:v:393:y:2014:i:c:p:560-570
    DOI: 10.1016/j.physa.2013.08.063
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    References listed on IDEAS

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    1. Gong, Maoguo & Ma, Lijia & Zhang, Qingfu & Jiao, Licheng, 2012. "Community detection in networks by using multiobjective evolutionary algorithm with decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 4050-4060.
    2. Yoo, Jaewan & Lee, J.S. & Kahng, B., 2011. "Disease spreading on fitness-rewired complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4571-4576.
    3. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    4. Ma, Xiaoke & Gao, Lin & Yong, Xuerong & Fu, Lidong, 2010. "Semi-supervised clustering algorithm for community structure detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 187-197.
    5. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    6. Salehi, Mostafa & Rabiee, Hamid R. & Jalili, Mahdi, 2010. "Motif structure and cooperation in real-world complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(23), pages 5521-5529.
    7. Blagus, Neli & Šubelj, Lovro & Bajec, Marko, 2012. "Self-similar scaling of density in complex real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2794-2802.
    8. Zou, Liuhua & Pei, Wenjiang & Li, Tao & He, Zhenya & Cheung, Yiuming, 2007. "Topological fractal networks introduced by mixed degree distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 592-600.
    9. Šubelj, Lovro & Bajec, Marko, 2011. "Community structure of complex software systems: Analysis and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2968-2975.
    10. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    11. Jalili, Mahdi, 2011. "Synchronizability of dynamical scale-free networks subject to random errors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4588-4595.
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