IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v475y2024ics0096300324001917.html
   My bibliography  Save this article

The competitive diffusion of knowledge and rumor in a multiplex network: A mathematical model

Author

Listed:
  • Huang, He
  • Pan, Jialin
  • Chen, Yahong

Abstract

The competition between rumor and knowledge has received significant attention from the global world. How to spread knowledge to better contain rumor has also become an important practical issue. In this study, we build a multi-compartment model in a multiplex network to study the competitive diffusion of knowledge and rumor. Two factors are emphasized in the model: penetration of knowledge into rumor, and spreading channel difference between knowledge and rumor. The model is further improved with the information-infected states divided into two sub-states: information-accepted and information-sharing. The mean-field method is adopted to analyze the model and then verified by the numerical results in both ER random networks and BA scale-free networks. The consistent results in ER and BA networks show that both rumor and knowledge thresholds are increased by the intensity of competition between them, and the rumor-knowledge competition goes through four phases: “no rumor and no knowledge”, “rumor outbreak and no knowledge” (rumor wins), “no rumor and knowledge outbreak” (knowledge wins), and “rumor vs knowledge” (rumor competes and coexists with knowledge), where the thresholds of rumor and knowledge act as the boundary of different phases. The different results in ER and BA networks show that rumor and knowledge are generally easier to break out in BA networks. But the BA rumor threshold may exceed the ER rumor threshold with the increase of rumor-knowledge competition, making rumor instead become difficult to break out in ER networks than that in BA networks, which infers that the hub nodes play very important roles in knowledge spreading. Based on the results, two types of management on rumor-knowledge competition are explored to control rumor and accelerate knowledge. Interestingly, critical values are discovered in both types of management, highlighting the importance of strengthening knowledge sharing and penetrating knowledge into rumor spreaders and listeners. The results reveal the management complexity of rumor-knowledge competition under different conditions.

Suggested Citation

  • Huang, He & Pan, Jialin & Chen, Yahong, 2024. "The competitive diffusion of knowledge and rumor in a multiplex network: A mathematical model," Applied Mathematics and Computation, Elsevier, vol. 475(C).
  • Handle: RePEc:eee:apmaco:v:475:y:2024:i:c:s0096300324001917
    DOI: 10.1016/j.amc.2024.128719
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300324001917
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2024.128719?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wu, Qingchu & Chen, Shufang, 2022. "Coupled simultaneous evolution of disease and information on multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    2. Xiang Li & Bocheng Hou & Wei Wang, 2021. "Competing Complex Information Spreading in Multiplex Social Network," Complexity, Hindawi, vol. 2021, pages 1-9, May.
    3. Huo, Liang’an & Yu, Yue, 2023. "The impact of the self-recognition ability and physical quality on coupled negative information-behavior-epidemic dynamics in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    4. Alam, Muntasir & Kuga, Kazuki & Tanimoto, Jun, 2019. "Three-strategy and four-strategy model of vaccination game introducing an intermediate protecting measure," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 408-422.
    5. Zhuang, Yun-Bei & Chen, J.J. & Li, Zhi-hong, 2017. "Modeling the cooperative and competitive contagions in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 141-151.
    6. Tatsukawa, Yuichi & Arefin, Md. Rajib & Utsumi, Shinobu & Kuga, Kazuki & Tanimoto, Jun, 2022. "Stochasticity of disease spreading derived from the microscopic simulation approach for various physical contact networks," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    7. Xia, Ling-Ling & Jiang, Guo-Ping & Song, Bo & Song, Yu-Rong, 2015. "Rumor spreading model considering hesitating mechanism in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 295-303.
    8. Li, WenYao & Xue, Xiaoyu & Pan, Liming & Lin, Tao & Wang, Wei, 2022. "Competing spreading dynamics in simplicial complex," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    9. Alam, Muntasir & Ida, Yuki & Tanimoto, Jun, 2021. "Abrupt epidemic outbreak could be well tackled by multiple pre-emptive provisions-A game approach considering structured and unstructured populations," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    10. Wang, Jia-zeng & Liu, Zeng-rong & Xu, Jianhua, 2007. "Epidemic spreading on uncorrelated heterogenous networks with non-uniform transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 715-721.
    11. Yang, Dong & Chow, Tommy W.S. & Zhong, Lu & Tian, Zhaoyang & Zhang, Qingpeng & Chen, Guanrong, 2018. "True and fake information spreading over the Facebook," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 984-994.
    12. J. Gu & W. Li & X. Cai, 2008. "The effect of the forget-remember mechanism on spreading," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(2), pages 247-255, March.
    13. Kabir, KM Ariful & Kuga, Kazuki & Tanimoto, Jun, 2020. "The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    14. Ma, Jing & Zhu, He, 2018. "Rumor diffusion in heterogeneous networks by considering the individuals’ subjective judgment and diverse characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 276-287.
    15. Yan Wang & Feng Qing & Jian-Ping Chai & Ye-Peng Ni & xiaoke xu, 2021. "Spreading Dynamics of a 2SIH2R, Rumor Spreading Model in the Homogeneous Network," Complexity, Hindawi, vol. 2021, pages 1-9, February.
    16. Fang, Fanshu & Ma, Jing & Li, Yanli, 2023. "The coevolution of the spread of a disease and competing opinions in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    17. Wang, Huan & Ma, Chuang & Chen, Han-Shuang & Zhang, Hai-Feng, 2021. "Effects of asymptomatic infection and self-initiated awareness on the coupled disease-awareness dynamics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    18. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    19. Kumar, Ajay & Swarnakar, Pradip & Jaiswal, Kamya & Kurele, Ritika, 2020. "SMIR model for controlling the spread of information in social networking sites," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jianhong Chen & Hongcai Ma & Shan Yang, 2023. "SEIOR Rumor Propagation Model Considering Hesitating Mechanism and Different Rumor-Refuting Ways in Complex Networks," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    2. Chen, Yahong & Huang, He, 2022. "Modeling the impacts of contact tracing on an epidemic with asymptomatic infection," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    3. Meng, Xueyu & Lin, Jianhong & Fan, Yufei & Gao, Fujuan & Fenoaltea, Enrico Maria & Cai, Zhiqiang & Si, Shubin, 2023. "Coupled disease-vaccination behavior dynamic analysis and its application in COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    4. Xia, Yang & Jiang, Haijun & Yu, Zhiyong, 2022. "Global dynamics of ILSR rumor spreading model with general nonlinear spreading rate in multi-lingual environment," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    5. Huang, He & Chen, Yahong & Ma, Yefeng, 2021. "Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading," Applied Mathematics and Computation, Elsevier, vol. 388(C).
    6. Yin, Fulian & Jiang, Xinyi & Qian, Xiqing & Xia, Xinyu & Pan, Yanyan & Wu, Jianhong, 2022. "Modeling and quantifying the influence of rumor and counter-rumor on information propagation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    7. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.
    8. Jinxian Li & Yanping Hu & Zhen Jin, 2019. "Rumor Spreading of an SIHR Model in Heterogeneous Networks Based on Probability Generating Function," Complexity, Hindawi, vol. 2019, pages 1-15, June.
    9. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The interplay of behaviors and attitudes in public goods game considering environmental investment," Applied Mathematics and Computation, Elsevier, vol. 382(C).
    10. Huang, He & Chen, Yahong & Yan, Zhijun, 2021. "Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model," Applied Mathematics and Computation, Elsevier, vol. 398(C).
    11. Tian, Yang & Tian, Hui & Cui, Qimei & Zhu, Xuzhen, 2024. "Phase transition phenomena in social propagation with dynamic fashion tendency and individual contact," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    12. Wang, Tao & He, Juanjuan & Wang, Xiaoxia, 2018. "An information spreading model based on online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 488-496.
    13. Lu, Peng & Deng, Liping & Liao, Hongbing, 2019. "Conditional effects of individual judgment heterogeneity in information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 335-344.
    14. Jia Wang & Zhiping Wang & Ping Yu & Peiwen Wang, 2022. "The SEIR Dynamic Evolutionary Model with Markov Chains in Hyper Networks," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    15. Huang, He & Xu, Yang & Xing, Jingli & Shi, Tianyu, 2023. "Social influence or risk perception? A mathematical model of self-protection against asymptomatic infection in multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    16. Zhang, Rongping & Liu, Maoxing & Xie, Boli, 2022. "The analysis of discrete-time epidemic model on networks with protective measures on game theory," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    17. Chen, Jian & Yang, Lu-Xing & Yang, Xiaofan & Tang, Yuan Yan, 2020. "Cost-effective anti-rumor message-pushing schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    18. Li, Tianyu & Wu, Yong & Ding, Qianming & Xie, Ying & Yu, Dong & Yang, Lijian & Jia, Ya, 2024. "Social contagion in high-order network with mutation," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    19. Cui, Guang-Hai & Wang, Zhen & Li, Jun-Li & Jin, Xing & Zhang, Zhi-Wang, 2021. "Influence of precaution and dynamic post-indemnity based insurance policy on controlling the propagation of epidemic security risks in networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    20. Li, Dandan & Xie, Weijie & Han, Dun, 2024. "Multi-information and epidemic coupling propagation considering indirect contact on two-layer networks," Applied Mathematics and Computation, Elsevier, vol. 474(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:475:y:2024:i:c:s0096300324001917. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.