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DSIR double-rumors spreading model in complex networks

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  • Zan, Yongli

Abstract

For there are always several kinds of rumors spreading simultaneously in real networks, the research about multiple rumors propagation process is necessary and significant. In this paper, considering the spread of two rumors with different launch time, and assuming the content of each rumor may have nothing to do with the others, we study the double-rumors concurrently spreading dynamics in complex networks, and introduce two kinds of double-rumors spreading models: the DSIR model and the C-DSIR model. We then provide the double-rumors dissemination mechanism by states-vectors expressions and derive the mean-field equations of models to describe their dynamics. Particularly, without rumors priorities, we introduce a selection parameter θ for spreaders to express the attractions of different rumors, and study the influence of this parameter on double-rumors spreading. Numerical simulations are performed to explore the interaction between two rumors, and we investigate the spreading peak and the final size of the rumors with various parameters. Simulation results indicate that, the best launch time of new rumor exists explicitly for the DSIR model, the selection parameter θ and the delay time Tin are interdependent quantities, and the closer the start time of new rumor is to the best time, the more obvious the interdependence would be. Meanwhile, Tin is also a network-dependent parameter for our models in a series of BA networks. Furthermore, under the same conditions, the influential nodes identified by large coreness are the relative better promulgators for new rumor, so they are what the strategy should give priorities to. Our experiment reveals some interesting patterns of double-rumors spreading and suggest a possible avenue for further study of interplays of multiple pieces of information in complex network.

Suggested Citation

  • Zan, Yongli, 2018. "DSIR double-rumors spreading model in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 191-202.
    • Handle: RePEc:eee:chsofr:v:110:y:2018:i:c:p:191-202
    DOI: 10.1016/j.chaos.2018.03.021
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    1. Villela, Daniel A.M., 2016. "Analysis of the vectorial capacity of vector-borne diseases using moment-generating functions," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 1-8.
    2. Wang, Jiajia & Zhao, Laijun & Huang, Rongbing, 2014. "2SI2R rumor spreading model in homogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 153-161.
    3. Xing, Yi & Song, Lipeng & Sun, Gui-Quan & Jin, Zhen & Zhang, Juan, 2017. "Assessing reappearance factors of H7N9 avian influenza in China," Applied Mathematics and Computation, Elsevier, vol. 309(C), pages 192-204.
    4. Zan, Yongli & Wu, Jianliang & Li, Ping & Yu, Qinglin, 2014. "SICR rumor spreading model in complex networks: Counterattack and self-resistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 159-170.
    5. Zhao, Dawei & Wang, Lianhai & Xu, Lijuan & Wang, Zhen, 2015. "Finding another yourself in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 599-604.
    6. Dawei Zhao & Lianhai Wang & Shudong Li & Zhen Wang & Lin Wang & Bo Gao, 2014. "Immunization of Epidemics in Multiplex Networks," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-5, November.
    7. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    8. Zhao, Dawei & Wang, Lianhai & Xu, Shujiang & Liu, Guangqi & Han, Xiaohui & Li, Shudong, 2017. "Vital layer nodes of multiplex networks for immunization and attack," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 169-175.
    9. Li, Li, 2015. "Patch invasion in a spatial epidemic model," Applied Mathematics and Computation, Elsevier, vol. 258(C), pages 342-349.
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    17. Hongying Xiao & Zhaofeng Li & Yuanyuan Zhang & Hong Lin & Yuxiao Zhao, 2023. "A Dual Rumor Spreading Model with Consideration of Fans versus Ordinary People," Mathematics, MDPI, vol. 11(13), pages 1-14, July.
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    21. Yin, Haofei & Zhang, Aobo & Zeng, An, 2023. "Identifying hidden target nodes for spreading in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
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    23. Li, Ming & Zhang, Hong & Georgescu, Paul & Li, Tan, 2021. "The stochastic evolution of a rumor spreading model with two distinct spread inhibiting and attitude adjusting mechanisms in a homogeneous social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).

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