IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v166y2023ics0960077922011389.html
   My bibliography  Save this article

Online public opinion dissemination model and simulation under media intervention from different perspectives

Author

Listed:
  • Geng, Lixiao
  • Zheng, Hongye
  • Qiao, Gaigai
  • Geng, Lisha
  • Wang, Ke

Abstract

This study investigates the influence of different media interventions on the dissemination of online public opinion, analyzes its laws, and provides a theoretical basis for the control of relevant departments. This study adds the influence of network media and government media on susceptible-exposed-infectious-removed (SEIR) model and considers the interaction between different emotions to construct the susceptible-exposed-positive-emotional-infectious-and-negative-emotional-infectious-immune-removed (SEI2R1R2) online public opinion dissemination model under such dual intervention of network media and government media. The opinion propagation model is simulated in Python and the model is validated by mining text sentiment using text convolutional neural networks (CNN) to fit relevant parameters. Results show that the SEI2R1R2 online public opinion dissemination model is more consistent with reality. With the role of media from different perspectives, identifying and controlling emotional communicators and increasing the probability of converting positive and negative emotional communicators into quitters can effectively reduce the number of communicators, and thus control the spread of public opinion.

Suggested Citation

  • Geng, Lixiao & Zheng, Hongye & Qiao, Gaigai & Geng, Lisha & Wang, Ke, 2023. "Online public opinion dissemination model and simulation under media intervention from different perspectives," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    • Handle: RePEc:eee:chsofr:v:166:y:2023:i:c:s0960077922011389
    DOI: 10.1016/j.chaos.2022.112959
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077922011389
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2022.112959?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. Huo, Liang’an & Ma, Chenyang, 2017. "The interaction evolution model of mass incidents with delay in a social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 440-452.
    2. 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.
    3. 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. 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.
    3. Huo, Liang’an & Song, Naixiang, 2016. "Dynamical interplay between the dissemination of scientific knowledge and rumor spreading in emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 73-84.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. Li, Dandan & Ma, Jing & Tian, Zihao & Zhu, Hengmin, 2015. "An evolutionary game for the diffusion of rumor in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 51-58.
    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. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. Robert J. Shiller, 2017. "Narrative Economics," American Economic Review, American Economic Association, vol. 107(4), pages 967-1004, April.
    16. 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.
    17. Wang, Xingxing & Li, Huajiao & Yao, Huajun & Zhu, Depeng & Liu, Nairong, 2018. "Simulation analysis of the spread of a supply crisis based on the global natural graphite trade network," Resources Policy, Elsevier, vol. 59(C), pages 200-209.
    18. Amaral, Marco A. & Oliveira, Marcelo M. de & Javarone, Marco A., 2021. "An epidemiological model with voluntary quarantine strategies governed by evolutionary game dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    19. Ketelaar, Paul E. & Janssen, Loes & Vergeer, Maurice & van Reijmersdal, Eva A. & Crutzen, Rik & van ‘t Riet, Jonathan, 2016. "The success of viral ads: Social and attitudinal predictors of consumer pass-on behavior on social network sites," Journal of Business Research, Elsevier, vol. 69(7), pages 2603-2613.
    20. 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.

    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:chsofr:v:166:y:2023:i:c:s0960077922011389. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.