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Partition signed social networks via clustering dynamics

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  • Wu, Jianshe
  • Zhang, Long
  • Li, Yong
  • Jiao, Yang

Abstract

Inspired by the dynamics phenomenon occurred in social networks, the WJJLGS model is modified to imitate the clustering dynamics of signed social networks. Analyses show that the clustering dynamics of the model can be applied to partition signed social networks. Traditionally, blockmodel is applied to partition signed networks. In this paper, a detailed dynamics-based algorithm for signed social networks (DBAS) is presented. Simulations on several typical real-world and illustrative networks that have been analyzed by the blockmodel verify the correctness of the proposed algorithm. The efficiency of the algorithm is verified on large scale synthetic networks.

Suggested Citation

  • Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
    • Handle: RePEc:eee:phsmap:v:443:y:2016:i:c:p:568-582
    DOI: 10.1016/j.physa.2015.09.066
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    References listed on IDEAS

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    1. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Overlapping community detection using neighborhood ratio matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 510-521.
    2. Kocheturov, Anton & Batsyn, Mikhail & Pardalos, Panos M., 2014. "Dynamics of cluster structures in a financial market network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 523-533.
    3. Qu, Yingfei & Shi, Weiren & Shi, Xin, 2015. "Inferring overlapping community structure with degree-corrected block model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 48-54.
    4. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Community detection using local neighborhood in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 665-677.
    5. Wu, Zhaoyan & Fu, Xinchu, 2014. "Cluster lag synchronisation in community networks via linear pinning control with local intermittent effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 487-498.
    6. Jillian J Jordan & David G Rand & Samuel Arbesman & James H Fowler & Nicholas A Christakis, 2013. "Contagion of Cooperation in Static and Fluid Social Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-10, June.
    7. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    8. Hu, Cheng & Jiang, Haijun, 2012. "Cluster synchronization for directed community networks via pinning partial schemes," Chaos, Solitons & Fractals, Elsevier, vol. 45(11), pages 1368-1377.
    9. G. Xu & S. Tsoka & L. G. Papageorgiou, 2007. "Finding community structures in complex networks using mixed integer optimisation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 60(2), pages 231-239, November.
    10. Wu, Jianshe & Lu, Rui & Jiao, Licheng & Liu, Fang & Yu, Xin & Wang, Da & Sun, Bo, 2013. "Phase transition model for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1287-1301.
    11. 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.
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    Cited by:

    1. Chen, Jianrui & Wang, Hua & Wang, Lina & Liu, Weiwei, 2016. "A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 482-492.
    2. Chen, Jianrui & Wei, Lidan & Uliji, & Zhang, Li, 2018. "Dynamic evolutionary clustering approach based on time weight and latent attributes for collaborative filtering recommendation," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 8-18.
    3. Ma, Yinghong & Zhu, Xiaoyu & Yu, Qinglin, 2019. "Clusters detection based leading eigenvector in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1263-1275.
    4. Zhu, Xiaoyu & Ma, Yinghong & Liu, Zhiyuan, 2018. "A novel evolutionary algorithm on communities detection in signed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 938-946.

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