IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v536y2019ics0378437119305722.html
   My bibliography  Save this article

Dynamical analysis of a IWSR rumor spreading model with considering the self-growth mechanism and indiscernible degree

Author

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

Abstract

Propagation of rumor, as one of the most important aspects of spreading dynamics on networks, which is often accompanied by the self-growth of individuals and indiscernible degree of events, and the analysis of this phenomenon can help us to better understand the information dissemination in the social network. Here, with the wiseman supplemented to the classical ignorant–spreader–stifler ( ISR) rumor spreading model, a modified ignorant–wiseman–spreader–stifler (IWSR) model is established with self-growth mechanism by considering indiscernible degree of events. By mean-field equations of IWSR model, the spreading thresholdλc is calculated to describe the theory of steady state dynamics of the rumor spreading. Numerical simulation is performed to assess the influence of self-growth of individual and indiscernible degree of events on dynamic spreading process. The results show that when the spreading rate λ is smaller than the threshold λc, the rumor will not spread in the population; the stronger the self-growth ability of the individual is, the smaller the range of rumor will be; the higher the indiscernible degree of events is, the greater influence of the rumor; These obtained findings in the present study could not only elaborate our understandings of spreading dynamics in network, but also provide us with an insight to develop effective strategies of inhibiting rumor propagation.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119305722
    DOI: 10.1016/j.physa.2019.04.176
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119305722
    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.2019.04.176?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. Yi Zhang & Jiuping Xu & Yue Wu, 2018. "A fuzzy rumor spreading model based on transmission capacity," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-21, February.
    2. Ya-Qi Wang & Jing Wang, 2017. "SIR rumor spreading model considering the effect of difference in nodes’ identification capabilities," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(05), pages 1-15, May.
    3. Liang'an Huo & Tingting Lin & Peiqing Huang, 2013. "Dynamical Behavior of a Rumor Transmission Model with Psychological Effect in Emergency Event," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-9, December.
    4. 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.
    5. 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.
    6. Liu, Qiming & Li, Tao & Sun, Meici, 2017. "The analysis of an SEIR rumor propagation model on heterogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 372-380.
    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. Zhao, Laijun & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli & Wang, Jiajia, 2013. "SIR rumor spreading model in the new media age," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 995-1003.
    9. Huo, Liang'an & Wang, Li & Song, Naixiang & Ma, Chenyang & He, Bing, 2017. "Rumor spreading model considering the activity of spreaders in the homogeneous network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 855-865.
    10. 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.
    11. Jiuping Xu & Yi Zhang, 2015. "Event ambiguity fuels the effective spread of rumors," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-16.
    12. Zhao, Laijun & Qiu, Xiaoyan & Wang, Xiaoli & Wang, Jiajia, 2013. "Rumor spreading model considering forgetting and remembering mechanisms in inhomogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 987-994.
    13. Galam, Serge, 2003. "Modelling rumors: the no plane Pentagon French hoax case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 571-580.
    14. 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.
    15. Fan, Chong-jun & Jin, Yang & Huo, Liang-an & Liu, Chen & Yang, Yun-peng & Wang, Ya-qiong, 2016. "Effect of individual behavior on the interplay between awareness and disease spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 523-530.
    16. Wang, Jiajia & Zhao, Laijun & Huang, Rongbing, 2014. "SIRaRu rumor spreading model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 43-55.
    17. Afassinou, Komi, 2014. "Analysis of the impact of education rate on the rumor spreading mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 43-52.
    18. Zhao, Laijun & Wang, Jiajia & Chen, Yucheng & Wang, Qin & Cheng, Jingjing & Cui, Hongxin, 2012. "SIHR rumor spreading model in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2444-2453.
    19. 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.
    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. Wenjia Liu & Jian Wang & Yanfeng Ouyang, 2022. "Rumor Transmission in Online Social Networks Under Nash Equilibrium of a Psychological Decision Game," Networks and Spatial Economics, Springer, vol. 22(4), pages 831-854, December.
    2. 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.

    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. 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.
    5. 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.
    6. Yao Hongxing & Gao Xiangyang, 2018. "SE2IR Invest Market Rumor Spreading Model Considering Hesitating Mechanism," Journal of Systems Science and Information, De Gruyter, vol. 7(1), pages 54-69, March.
    7. 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).
    8. 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).
    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. Huo, Liang’an & Jiang, Jiehui & Gong, Sixing & He, Bing, 2016. "Dynamical behavior of a rumor transmission model with Holling-type II functional response in emergency event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 228-240.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Jie, Renlong & Qiao, Jian & Xu, Genjiu & Meng, Yingying, 2016. "A study on the interaction between two rumors in homogeneous complex networks under symmetric conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 129-142.
    20. Lan, Yuexin & Lian, Zhixuan & Zeng, Runxi & Zhu, Di & Xia, Yixue & Liu, Mo & Zhang, Peng, 2020. "A statistical model of the impact of online rumors on the information quantity of online public opinion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(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:536:y:2019:i:c:s0378437119305722. 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.