IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v559y2020ics0378437120305562.html
   My bibliography  Save this article

Rumor spreading in complex networks under stochastic node activity

Author

Listed:
  • Cheng, Yingying
  • Huo, Liang’an
  • Zhao, Laijun

Abstract

The research on rumor spreading has a long history, and its wanton flooding has brought huge impact on people’s life. In the process of its spreading, the individual’s activity plays an important role. However, in the complex and changeable environment, randomness cannot be ignored, not to mention its influence on individual activity Based on the ISR model of individual activity, this paper explores the stochastic version of the rumor model including fluctuations in the activity. Then, the influence of Stratonovich stochastic noise on the asymptotic behavior of non-linear rumor spreading model is studied. Through the mathematical analysis, we get the critical values to measure whether the deterministic and stochastics models spread or not, as well as the threshold conditions for rumor to spread wantonly. At the same time, the effects of Stratonovich stochastic noise on the asymptotic behavior of rumor-free equilibrium point E0 and endemic equilibrium point E∗ are obtained respectively, and the condition that the rumor-free equilibrium is globally asymptotically stable in the presence of noise is given. Finally, the theoretical results are verified by numerical simulation.

Suggested Citation

  • Cheng, Yingying & Huo, Liang’an & Zhao, Laijun, 2020. "Rumor spreading in complex networks under stochastic node activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    • Handle: RePEc:eee:phsmap:v:559:y:2020:i:c:s0378437120305562
    DOI: 10.1016/j.physa.2020.125061
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120305562
    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.2020.125061?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. Jain, Ankur & Dhar, Joydip & Gupta, Vijay, 2019. "Stochastic model of rumor propagation dynamics on homogeneous social network with expert interaction and fluctuations in contact transmissions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 227-236.
    2. Liang’an Huo & Tingting Lin & Chen Liu & Xing Fang, 2019. "How the node’s vital and tie strength effect rumor spreading on social network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(06), pages 1-13, June.
    3. Liu, Xiongding & Li, Tao & Xu, Hao & Liu, Wenjin, 2019. "Spreading dynamics of an online social information model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 497-510.
    4. Chen, Guanghua, 2019. "ILSCR rumor spreading model to discuss the control of rumor spreading in emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 88-97.
    5. Jiayang Li & Jiafu Tang & Dan Wang, 2019. "Dynamic Spreading Model of Passenger Group Panic considering Official Guidance Information in Subway Emergencies," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-17, October.
    6. Amirhosein Bodaghi & Sama Goliaei, 2018. "A Novel Model For Rumor Spreading On Social Networks With Considering The Influence Of Dissenting Opinions," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-24, September.
    7. Liu, Chen & Zhou, Li-xin & Fan, Chong-jun & Huo, Liang-an & Tian, Zhan-wei, 2015. "Activity of nodes reshapes the critical threshold of spreading dynamics in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 269-278.
    8. Zhu, Liang & Wang, Youguo, 2017. "Rumor spreading model with noise interference in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 750-760.
    9. Dauhoo, Muhammad Zaid & Juggurnath, Diksha & Badurally Adam, Noure-Roukayya, 2016. "The stochastic evolution of rumors within a population," Mathematical Social Sciences, Elsevier, vol. 82(C), pages 85-96.
    10. Xu, Hao & Li, Tao & Liu, Xiongding & Liu, Wenjin & Dong, Jing, 2019. "Spreading dynamics of an online social rumor model with psychological factors on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 234-246.
    11. Jia, Fangju & Lv, Guangying, 2018. "Dynamic analysis of a stochastic rumor propagation model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 613-623.
    12. Tornatore, Elisabetta & Maria Buccellato, Stefania & Vetro, Pasquale, 2005. "Stability of a stochastic SIR system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 111-126.
    13. Huo, Liang’an & Cheng, Yingying & Liu, Chen & Ding, Fan, 2018. "Dynamic analysis of rumor spreading model for considering active network nodes and nonlinear spreading rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 24-35.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. 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.

    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. 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).
    2. 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).
    3. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.
    4. 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.
    5. Hou, Jingrui & Chi, Ming & Li, Tao & Guan, Zhi-Hong & Luo, Kai & Zhang, Ding-Xue, 2019. "Spreading dynamics of SVFR online fraud information model on heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Sahafizadeh, Ebrahim & Tork Ladani, Behrouz, 2023. "Soft rumor control in mobile instant messengers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    7. Jain, Ankur & Dhar, Joydip & Gupta, Vijay, 2019. "Stochastic model of rumor propagation dynamics on homogeneous social network with expert interaction and fluctuations in contact transmissions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 227-236.
    8. Lu, Peng & Yao, Qi & Lu, Pengfei, 2019. "Two-stage predictions of evolutionary dynamics during the rumor dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 349-369.
    9. Yanhui Wei & Liang’an Huo & Hongguang He, 2022. "Research on Rumor-Spreading Model with Holling Type III Functional Response," Mathematics, MDPI, vol. 10(4), pages 1-13, February.
    10. 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).
    11. 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).
    12. Li, Shuang & Xiong, Jie, 2024. "SIR epidemic model with non-Lipschitz stochastic perturbations," Statistics & Probability Letters, Elsevier, vol. 210(C).
    13. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    14. 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.
    15. William Brock & Anastasios Xepapadeas, 2020. "The Economy, Climate Change and Infectious Diseases: Links and Policy Implications," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 811-824, August.
    16. Zhiming Li & Zhidong Teng, 2019. "Analysis of uncertain SIS epidemic model with nonlinear incidence and demography," Fuzzy Optimization and Decision Making, Springer, vol. 18(4), pages 475-491, December.
    17. Liu, Qun & Jiang, Daqing & Shi, Ningzhong & Hayat, Tasawar & Ahmad, Bashir, 2017. "Stationary distribution and extinction of a stochastic SEIR epidemic model with standard incidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 476(C), pages 58-69.
    18. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.
    19. Lahrouz, Aadil & Omari, Lahcen, 2013. "Extinction and stationary distribution of a stochastic SIRS epidemic model with non-linear incidence," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 960-968.
    20. Yu, Shuzhen & Yu, Zhiyong & Jiang, Haijun, 2024. "A rumor propagation model in multilingual environment with time and state dependent impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 182(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:559:y:2020:i:c:s0378437120305562. 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: 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.