IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v531y2019ics0378437119310386.html
   My bibliography  Save this article

ILSR rumor spreading model with degree in complex network

Author

Listed:
  • Yang, Anzhi
  • Huang, Xianying
  • Cai, Xiumei
  • Zhu, Xiaofei
  • Lu, Ling

Abstract

Most rumors in social networks are extremely harmful and have a significant negative impact on social welfare. Therefore, exploring the laws of rumor propagation has been one of the hot topics in current researches. Most traditional rumor spreading models are based on infectious disease transmission models, such as SIR. Since the influence of individual differences and the network structure on rumor spreading are not considered, the rumor propagation process in complex networks can only be described in a coarse-grained manner. In this paper, we consider the role of different users in rumor propagation. Based on the degree of different nodes in the network, we design a new state transition function for each node and proposed a new rumor propagation ILSR model. Firstly, we analyze the model, calculate the equilibrium point and the basic reproductive number to prove the rationality of the model. Then experiments are performed in WS networks, BA scale-free networks and a real Facebook network to investigate the relationship between various nodes with time and the impact of network structure on rumor propagation, and the experimental results show the correctness and effectiveness of the model. It provides a reference for exploring the propagation law of rumors in complex networks and guiding and controlling the propagation of rumors.

Suggested Citation

  • Yang, Anzhi & Huang, Xianying & Cai, Xiumei & Zhu, Xiaofei & Lu, Ling, 2019. "ILSR rumor spreading model with degree in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119310386
    DOI: 10.1016/j.physa.2019.121807
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119310386
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.121807?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huo, Liang’an & Chen, Sijing, 2020. "Rumor propagation model with consideration of scientific knowledge level and social reinforcement in heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    2. 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).
    3. Ding, Haixin & Xie, Li, 2023. "Simulating rumor spreading and rebuttal strategy with rebuttal forgetting: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    4. Maia, Hugo P. & Ferreira, Silvio C. & Martins, Marcelo L., 2023. "Controversy-seeking fuels rumor-telling activity in polarized opinion networks," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    5. 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).
    6. Du, Yuxian & Lin, Xi & Pan, Ye & Chen, Zhaoxin & Xia, Huan & Luo, Qian, 2023. "Identifying influential airports in airline network based on failure risk factors with TOPSIS," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    7. 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.
    8. Liang’an Huo & Yuqing Zhang, 2022. "Effect of Global and Local Refutation Mechanism on Rumor Propagation in Heterogeneous Network," Mathematics, MDPI, vol. 10(4), pages 1-17, February.
    9. Wang, Jinling & Jiang, Haijun & Hu, Cheng & Yu, Zhiyong & Li, Jiarong, 2021. "Stability and Hopf bifurcation analysis of multi-lingual rumor spreading model with nonlinear inhibition mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    10. Javier Cifuentes-Faura & Ursula Faura-Martínez & Matilde Lafuente-Lechuga, 2022. "Mathematical Modeling and the Use of Network Models as Epidemiological Tools," Mathematics, MDPI, vol. 10(18), pages 1-14, September.
    11. Sahafizadeh, Ebrahim & Tork Ladani, Behrouz, 2023. "Soft rumor control in mobile instant messengers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Yin, Haofei & Zhang, Aobo & Zeng, An, 2023. "Identifying hidden target nodes for spreading in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    13. Tong Chen & Ziqing Chen & Xuejun Jin, 2021. "A multiple information model incorporating limited attention and information environment," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-22, October.
    14. 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).
    15. Jiang, Guoyin & Li, Saipeng & Li, Minglei, 2020. "Dynamic rumor spreading of public opinion reversal on Weibo based on a two-stage SPNR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(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:phsmap:v:531:y:2019:i:c:s0378437119310386. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.