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Exploring the dynamic growth mechanism of social networks using evolutionary hypergraph

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  • Wang, Zhiping
  • Yin, Haofei
  • Jiang, Xin

Abstract

An evolutionary hypernetwork model is proposed to describe the non-uniform evolution of social networks, in which nodes represent individuals while hyperedges represent relationships among individuals. The number of nodes in a hyperedge is a random integer. And the evolving process includes the addition of new nodes, linking of old nodes, and rewiring of links. By using Poisson process theory and the continuous method, we proved that the stationary average hyperdegree distribution follows the shifted power law (SPL). The theoretical analysis agree with the numerical simulations. Our model is universal, the fitness model in complex networks and scale-free model in hypernetworks can all be regarded as degradation cases of the model.

Suggested Citation

  • Wang, Zhiping & Yin, Haofei & Jiang, Xin, 2020. "Exploring the dynamic growth mechanism of social networks using evolutionary hypergraph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    • Handle: RePEc:eee:phsmap:v:544:y:2020:i:c:s0378437119314566
    DOI: 10.1016/j.physa.2019.122545
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    References listed on IDEAS

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    1. Zhou, Bin & Yan, Xiao-Yong & Xu, Xiao-Ke & Xu, Xiao-Ting & Wang, Nianxin, 2018. "Evolutionary of online social networks driven by pareto wealth distribution and bidirectional preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 427-434.
    2. Golzardi, Elaheh & Sheikhahmadi, Amir & Abdollahpouri, Alireza, 2019. "Detection of trust links on social networks using dynamic features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    3. Chang, Hui & Su, Bei-Bei & Zhou, Yue-Ping & He, Da-Ren, 2007. "Assortativity and act degree distribution of some collaboration networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 687-702.
    4. Shen, Ai-Zhong & Guo, Jin-Li & Suo, Qi, 2017. "Study of the variable growth hypernetworks influence on the scaling law," Chaos, Solitons & Fractals, Elsevier, vol. 97(C), pages 84-89.
    5. Li, Dong & Wang, Wei & Jin, Changlong & Ma, Jun & Sun, Xin & Xu, Zhiming & Li, Sheng & Liu, Jiming, 2019. "User recommendation for promoting information diffusion in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Suo, Qi & Guo, Jin-Li & Sun, Shiwei & Liu, Han, 2018. "Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 141-148.
    7. Yang, Dingda & Liao, Xiangwen & Shen, Huawei & Cheng, Xueqi & Chen, Guolong, 2018. "Modeling the reemergence of information diffusion in social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1493-1500.
    8. Seidman, Stephen B., 1981. "Structures induced by collections of subsets: a hypergraph approach," Mathematical Social Sciences, Elsevier, vol. 1(4), pages 381-396, August.
    9. Jiang, Xin & Wang, Zhiping & Liu, Wei, 2019. "Information dissemination in dynamic hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    10. Jian-Wei Wang & Li-Li Rong & Qiu-Hong Deng & Ji-Yong Zhang, 2010. "Evolving hypernetwork model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 493-498, October.
    11. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    12. Estrada, Ernesto & Rodríguez-Velázquez, Juan A., 2006. "Subgraph centrality and clustering in complex hyper-networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 581-594.
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    Cited by:

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