IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v461y2016icp569-576.html
   My bibliography  Save this article

Rumor spreading models with random denials

Author

Listed:
  • Giorno, Virginia
  • Spina, Serena

Abstract

The concept of denial is introduced on rumor spreading processes. The denials occur with a certain rate and they reset to start the initial situation. A population of N individuals is subdivided into ignorants, spreaders and stiflers; at the initial time there is only one spreader and the rest of the population is ignorant. The denials are introduced in the classic DK model and in its generalization, in which a spreader can transmit the rumor at most to k ignorants. The steady state densities are analyzed for these models. Finally, a numerical analysis is performed to study the rule of the involved parameters and to compare the proposed models.

Suggested Citation

  • Giorno, Virginia & Spina, Serena, 2016. "Rumor spreading models with random denials," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 569-576.
  • Handle: RePEc:eee:phsmap:v:461:y:2016:i:c:p:569-576
    DOI: 10.1016/j.physa.2016.06.070
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116303387
    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.2016.06.070?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. Noymer, Andrew, 2001. "The Transmission and Persistence of`'Urban Legends': Sociological Application of Age-Structured Epidemic Models," Center for Culture, Organizations and Politics, Working Paper Series qt0rv3c82q, Center for Culture, Organizations and Politics of theInstitute for Research on Labor and Employment, UC Berkeley.
    2. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    3. 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.
    4. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    5. 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.
    6. 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.
    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. Tingqiang Chen & Lei Wang & Jining Wang & Qi Yang, 2017. "A Network Diffusion Model of Food Safety Scare Behavior considering Information Transparency," Complexity, Hindawi, vol. 2017, pages 1-16, December.
    2. Antonio Di Crescenzo & Paola Paraggio & Serena Spina, 2023. "Stochastic Growth Models for the Spreading of Fake News," Mathematics, MDPI, vol. 11(16), pages 1-23, August.
    3. 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.
    4. Maria Gamboa & Maria Jesus Lopez-Herrero, 2018. "On the Number of Periodic Inspections During Outbreaks of Discrete-Time Stochastic SIS Epidemic Models," Mathematics, MDPI, vol. 6(8), pages 1-13, July.
    5. 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.
    6. Tian, Gang & Wang, Yumeng & Gong, Yu & Tian, Yi & Piao, Xuexu & Zhang, Tianyu, 2024. "The contagion mechanism and governance strategy of corporate social irresponsibility of Chinese food companies," Food Policy, Elsevier, vol. 122(C).
    7. Qi Yang & Yuejuan Hou & Haoran Wei & Tingqiang Chen & Jining Wang, 2022. "Nonlinear Diffusion Evolution Model of Unethical Behavior among Green Food Enterprise," Sustainability, MDPI, vol. 14(23), pages 1-22, December.
    8. Carlo Bianca & Marco Menale, 2020. "Mathematical Analysis of a Thermostatted Equation with a Discrete Real Activity Variable," Mathematics, MDPI, vol. 8(1), pages 1-8, January.
    9. 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.
    10. 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).
    11. Lu, Peng, 2019. "Heterogeneity, judgment, and social trust of agents in rumor spreading," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 447-461.

    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. 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.
    2. 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).
    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. 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).
    5. 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.
    6. Su, Qiang & Huang, Jiajia & Zhao, Xiande, 2015. "An information propagation model considering incomplete reading behavior in microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 55-63.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. Wang, Jiajia & Zhao, Laijun & Huang, Rongbing, 2014. "2SI2R rumor spreading model in homogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 153-161.
    12. Dayan, Fazal & Rafiq, Muhammad & Ahmed, Nauman & Baleanu, Dumitru & Raza, Ali & Ahmad, Muhammad Ozair & Iqbal, Muhammad, 2022. "Design and numerical analysis of fuzzy nonstandard computational methods for the solution of rumor based fuzzy epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    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. 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.
    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).
    16. Carlo Kopp & Kevin B Korb & Bruce I Mills, 2018. "Information-theoretic models of deception: Modelling cooperation and diffusion in populations exposed to "fake news"," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-35, November.
    17. Cui, Yapeng & Ni, Shunjiang & Shen, Shifei & Wang, Zhiru, 2020. "Modeling the dynamics of information dissemination under disaster," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    18. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    19. 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.
    20. 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.

    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:461:y:2016:i:c:p:569-576. 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.