IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v5y2017i6p571-584n6.html
   My bibliography  Save this article

Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism

Author

Listed:
  • Chen Jianhong

    (School of Resources and Safety Engineering, Central South University, Changsha410083, China)

  • Song Qinghua

    (School of Resources and Safety Engineering, Central South University, Changsha410083, China)

  • Zhou Zhiyong

    (School of Resources and Safety Engineering, Central South University, Changsha410083, China)

Abstract

To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.

Suggested Citation

  • Chen Jianhong & Song Qinghua & Zhou Zhiyong, 2017. "Agent-Based Simulation of Rumor Propagation on Social Network Based on Active Immune Mechanism," Journal of Systems Science and Information, De Gruyter, vol. 5(6), pages 571-584, December.
  • Handle: RePEc:bpj:jossai:v:5:y:2017:i:6:p:571-584:n:6
    DOI: 10.21078/JSSI-2017-571-14
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2017-571-14
    Download Restriction: no

    File URL: https://libkey.io/10.21078/JSSI-2017-571-14?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
    ---><---

    References listed on IDEAS

    as
    1. Ma, Jing & Li, Dandan & Tian, Zihao, 2016. "Rumor spreading in online social networks by considering the bipolar social reinforcement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 108-115.
    2. Laijun Zhao & Jiajia Wang & Rongbing Huang, 2015. "Immunization against the Spread of Rumors in Homogenous Networks," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    3. 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.
    4. Zhang, Nan & Huang, Hong & Su, Boni & Zhao, Jinlong & Zhang, Bo, 2014. "Dynamic 8-state ICSAR rumor propagation model considering official rumor refutation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 333-346.
    5. Zhao, Laijun & Xie, Wanlin & Gao, H. Oliver & Qiu, Xiaoyan & Wang, Xiaoli & Zhang, Shuhai, 2013. "A rumor spreading model with variable forgetting rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6146-6154.
    6. Zhao, Laijun & Wang, Xiaoli & Qiu, Xiaoyan & Wang, Jiajia, 2013. "A model for the spread of rumors in Barrat–Barthelemy–Vespignani (BBV) networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5542-5551.
    7. Han, Shuo & Zhuang, Fuzhen & He, Qing & Shi, Zhongzhi & Ao, Xiang, 2014. "Energy model for rumor propagation on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 99-109.
    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. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.
    2. 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.
    3. 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.
    4. Linhe Zhu & Hongyong Zhao, 2017. "Dynamical behaviours and control measures of rumour-spreading model with consideration of network topology," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(10), pages 2064-2078, July.
    5. 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.
    6. Li, Dandan & Ma, Jing, 2017. "How the government’s punishment and individual’s sensitivity affect the rumor spreading in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 284-292.
    7. Jia, Pingqi & Wang, Chao & Zhang, Gaoyu & Ma, Jianfeng, 2019. "A rumor spreading model based on two propagation channels in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 342-353.
    8. Shuzhen Yu & Zhiyong Yu & Haijun Jiang, 2022. "Stability, Hopf Bifurcation and Optimal Control of Multilingual Rumor-Spreading Model with Isolation Mechanism," Mathematics, MDPI, vol. 10(23), pages 1-29, December.
    9. Pan, Cheng & Yang, Lu-Xing & Yang, Xiaofan & Wu, Yingbo & Tang, Yuan Yan, 2018. "An effective rumor-containing strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 80-91.
    10. Yu, Shuzhen & Yu, Zhiyong & Jiang, Haijun & Li, Jiarong, 2021. "Dynamical study and event-triggered impulsive control of rumor propagation model on heterogeneous social network incorporating delay," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    11. Zhang, Yuhuai & Zhu, Jianjun, 2018. "Stability analysis of I2S2R rumor spreading model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 862-881.
    12. Hu, Yuhan & Pan, Qiuhui & Hou, Wenbing & He, Mingfeng, 2018. "Rumor spreading model considering the proportion of wisemen in the crowd," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1084-1094.
    13. Huo, Liang’an & Cheng, Yingying, 2019. "Dynamical analysis of a IWSR rumor spreading model with considering the self-growth mechanism and indiscernible degree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Tian, Yong & Ding, Xuejun, 2019. "Rumor spreading model with considering debunking behavior in emergencies," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    15. 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).
    16. Hosni, Adil Imad Eddine & Li, Kan & Ahmad, Sadique, 2020. "Analysis of the impact of online social networks addiction on the propagation of rumors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    17. 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).
    18. Wang, Jinling & Jiang, Haijun & Ma, Tianlong & Hu, Cheng, 2019. "Global dynamics of the multi-lingual SIR rumor spreading model with cross-transmitted mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 148-157.
    19. Zhu, He & Ma, Jing, 2019. "Analysis of SHIR rumor propagation in random heterogeneous networks with dynamic friendships," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 257-271.
    20. Yao, Yao & Xiao, Xi & Zhang, Chengping & Dou, Changsheng & Xia, Shutao, 2019. "Stability analysis of an SDILR model based on rumor recurrence on social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(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:bpj:jossai:v:5:y:2017:i:6:p:571-584:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.