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MM-SIS: Model for multiple information spreading in multiplex network

Author

Listed:
  • Xiao, Yunpeng
  • Zhang, Li
  • Li, Qian
  • Liu, Ling

Abstract

In social networks, relationships between information are complexly intertwined. However, prior research mainly focuses on studying the independent information in an isolated network, ignoring two factors: the interaction between different information and the diversity of propagation paths. In view of the above problems, this paper proposes the MM-SIS(Multiple information and Multiplex network-SIS)model to explore the detailed processes and characteristics of multiple information in multiplex networks. At the same time, the concept of influence factor is introduced to describe the complex interaction between different information. Moreover, we use the Microscopic Markov Chain method to set dynamic equations, theoretically analyze the epidemic threshold and verify its correctness through experiments. In general, this paper mainly explores the effects of influence factor and the interrelation of network layers on information spreading process. The experimental results show that the above mentioned two factors have obvious impacts on the information outbreak scale and the epidemic threshold.

Suggested Citation

  • Xiao, Yunpeng & Zhang, Li & Li, Qian & Liu, Ling, 2019. "MM-SIS: Model for multiple information spreading in multiplex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 135-146.
    • Handle: RePEc:eee:phsmap:v:513:y:2019:i:c:p:135-146
    DOI: 10.1016/j.physa.2018.08.169
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    References listed on IDEAS

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    Cited by:

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    2. Changheng Shao & Fengjing Shao & Xin Liu & Dawei Yang & Rencheng Sun & Lili Zhang & Kaiwen Jiang, 2024. "A Multi-Information Dissemination Model Based on Cellular Automata," Mathematics, MDPI, vol. 12(6), pages 1-17, March.
    3. Yao, Yao & Li, Yuanyuan & Xiong, Xi & Wu, Yue & Lin, Honggang & Ju, Shenggen, 2020. "An interactive propagation model of multiple information in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    4. Sameera Horawalavithana & Nazim Choudhury & John Skvoretz & Adriana Iamnitchi, 2022. "Online discussion threads as conversation pools: predicting the growth of discussion threads on reddit," Computational and Mathematical Organization Theory, Springer, vol. 28(2), pages 112-140, June.
    5. Zhang, Jing & Wang, Xiaoli & Xie, Yanxi & Wang, Meihua, 2022. "Research on multi-topic network public opinion propagation model with time delay in emergencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

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