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Information dissemination in dynamic hypernetwork

Author

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  • Jiang, Xin
  • Wang, Zhiping
  • Liu, Wei

Abstract

Recently, the information diffusion models based on static hypernetworks have been proposed, in which the nodes and hyperedges represent the individuals and the social groups consisting of several individuals, respectively. However, the social networks represented by hypernetwork should be a dynamic network because of social activities. Hence, we establish an SIS model to present the dynamics of information spreading in a dynamic social hypernetworks with three dynamic processes. Then the theoretical analysis and simulation of the model are carried out, and theoretical results are accordant with the simulation results. In addition, the effects of different parameters on the information dissemination dynamics are analyzed in RP and CP strategy respectively. Most noteworthy, reorganization of social relations leads to a decrease in the proportion of informed individuals in stable state. By analyzing the effect of hyperedge reorganization on hyperdegree distribution, we discover the reorganization result in the increasing number of isolated nodes. These isolated nodes is hard to be joined in new social relationships, and cannot get information from the social network.

Suggested Citation

  • Jiang, Xin & Wang, Zhiping & Liu, Wei, 2019. "Information dissemination in dynamic hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    • Handle: RePEc:eee:phsmap:v:532:y:2019:i:c:s037843711930932x
    DOI: 10.1016/j.physa.2019.121578
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    Citations

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    Cited by:

    1. Tan, Jipeng & Zhang, Man & Liu, Fengming, 2024. "Online-Offline Higher-Order Rumor Propagation Model Based on Quantum Cellular Automata Considering Social Adaptation," Applied Mathematics and Computation, Elsevier, vol. 461(C).
    2. Haosen Wang & Qingtao Pan & Jun Tang, 2024. "HEDV-Greedy: An Advanced Algorithm for Influence Maximization in Hypergraphs," Mathematics, MDPI, vol. 12(7), pages 1-18, March.
    3. Yu, Ping & Wang, Zhiping & Wang, Peiwen & Yin, Haofei & Wang, Jia, 2022. "Dynamic evolution of shipping network based on hypergraph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    4. Liu, Jiawei & Ding, Jie, 2020. "Requesting for retweeting or donating? A research on how the fundraiser seeks help in the social charitable crowdfunding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    5. Ping Yu & Zhiping Wang & Yanan Sun & Peiwen Wang, 2022. "Risk Diffusion and Control under Uncertain Information Based on Hypernetwork," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    6. 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).
    7. Zhang, Ziyu & Mei, Xuehui & Jiang, Haijun & Luo, Xupeng & Xia, Yang, 2023. "Dynamical analysis of Hyper-SIR rumor spreading model," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    8. Zhang, Dezhi & Zhang, Fangtao & Liang, Yijing, 2021. "An evolutionary model of the international logistics network based on the Belt and Road perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).

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