Research article

Official long-term and short-term strategies for preventing the spread of rumors

  • Received: 22 March 2023 Revised: 14 June 2023 Accepted: 25 June 2023 Published: 10 July 2023
  • Recently, public security incidents caused by rumor spreading have frequently occurred, leading to public panic, social chaos and even casualties. Therefore, how governments establish strategies to restrain rumor spreading is important for judging their governance capacity. Herein, we consider one long-term strategy (education) and two short-term strategies (isolation and debunking) for officials to intervene in rumor spreading. To investigate the effects of these strategies, an improved rumor-spreading model and a series of mean-field equations are proposed. Through theoretical analysis, the effective thresholds of three rumor-prevention strategies are obtained, respectively. Finally, through simulation analysis, the effectiveness of these strategies in preventing rumor spreading is investigated. The results indicate that long-term and short-term strategies are effective in suppressing rumor spreading. The greater the efforts of governments to suppress rumors, the smaller the final rumor size. The study also shows that the three strategies are the best when applied simultaneously. The government can adopt corresponding measures to suppress rumor spreading effectively.

    Citation: Jiajia Wang, Xiaoyan Qiu. Official long-term and short-term strategies for preventing the spread of rumors[J]. Electronic Research Archive, 2023, 31(8): 4862-4881. doi: 10.3934/era.2023249

    Related Papers:

  • Recently, public security incidents caused by rumor spreading have frequently occurred, leading to public panic, social chaos and even casualties. Therefore, how governments establish strategies to restrain rumor spreading is important for judging their governance capacity. Herein, we consider one long-term strategy (education) and two short-term strategies (isolation and debunking) for officials to intervene in rumor spreading. To investigate the effects of these strategies, an improved rumor-spreading model and a series of mean-field equations are proposed. Through theoretical analysis, the effective thresholds of three rumor-prevention strategies are obtained, respectively. Finally, through simulation analysis, the effectiveness of these strategies in preventing rumor spreading is investigated. The results indicate that long-term and short-term strategies are effective in suppressing rumor spreading. The greater the efforts of governments to suppress rumors, the smaller the final rumor size. The study also shows that the three strategies are the best when applied simultaneously. The government can adopt corresponding measures to suppress rumor spreading effectively.



    加载中


    [1] D. J. Daley, D. G. Kendall, Stochastic rumours, IMA J. Appl. Math., 1 (1965), 42–55. https://doi.org/10.1093/imamat/1.1.42 doi: 10.1093/imamat/1.1.42
    [2] D. P. Maki, M. Thompson, Mathematical Models and Applications, with Emphasis on Social, Life, and Management Sciences, Englewood Cliffs, New Jersey, Prentice-Hall, 1973.
    [3] Y. Moreno, M. Nekovee, A. F. Pacheco, Dynamics of rumor spreading in complex networks, Phys. Rev. E, 69 (2004), 066130. https://doi.org/10.1103/PhysRevE.69.066130 doi: 10.1103/PhysRevE.69.066130
    [4] L. Zhu, H. Zhao, Dynamical behaviors and control measures of rumour-spreading model with consideration of network topology, Int. J. Syst. Sci., 48 (2017), 2064–2078. https://doi.org/10.1080/00207721.2017.1312628 doi: 10.1080/00207721.2017.1312628
    [5] L. Zhao, J. Wang, Y. C. Chen, Q. Wang, J. Cheng, H. Cui, SIHR rumor spreading model in social networks, Physica A, 391 (2012), 2444–2453. https://doi.org/10.1016/j.physa.2011.12.008 doi: 10.1016/j.physa.2011.12.008
    [6] S. Yu, Z. Yu, H. Jiang, S. Yang, The dynamics and control of 2I2SR rumor spreading models in multilingual online social networks, Inf. Sci., 581 (2021), 18–41. https://doi.org/10.1016/j.ins.2021.08.096 doi: 10.1016/j.ins.2021.08.096
    [7] Z. Dang, L. Li, W. Ni, R. Liu, H. Peng, Y. Yang, How does rumor spreading affect people inside and outside an institution, Inf. Sci., 574 (2021), 377–393. https://doi.org/10.1016/j.ins.2021.05.085 doi: 10.1016/j.ins.2021.05.085
    [8] W. Jing, Y. Li, X. Zhang, J. Zhang, Z. Jin, A rumor spreading pairwise model on weighted networks, Physica A, 585 (2022), 126451. https://doi.org/10.1016/j.physa.2021.126451 doi: 10.1016/j.physa.2021.126451
    [9] Z. Zhang, X. Mei, H. Jiang, X. Luo, Y. Xia, Dynamical analysis of Hyper-SIR rumor spreading model, Appl. Math. Comput., 446 (2023), 127887. https://doi.org/10.1016/j.amc.2023.127887 doi: 10.1016/j.amc.2023.127887
    [10] X. Chen, N. Wang, Rumor spreading model considering rumor credibility, correlation and crowd classification based on personality, Sci. Rep., 10 (2020), 5887. https://doi.org/10.1038/s41598-020-62585-9 doi: 10.1038/s41598-020-62585-9
    [11] A. I. E. Hosni, K. Li, S. Ahmad, Minimizing rumor influence in multiplex online social networks based on human individual and social behaviors, Inf. Sci., 512 (2020), 1458–1480. https://doi.org/10.1016/j.ins.2019.10.063 doi: 10.1016/j.ins.2019.10.063
    [12] Y. Cheng, L. Huo, L. Zhao, Dynamical behaviors and control measures of rumor-spreading model in consideration of the infected media and time delay, Inf. Sci., 564 (2021), 237–253. https://doi.org/10.1016/j.ins.2021.02.047 doi: 10.1016/j.ins.2021.02.047
    [13] C. Budak, D. Agrawal, A. E. Abbadi, Limiting the spread of misinformation in social networks, in Proceedings of the 20th International Conference on World Wide Web, Hyderabad, India, (2011), 665–674. https://doi.org/10.1145/1963405.1963499
    [14] R. M. Tripathy, A. Bagchi, S. Mehta, A study of rumor control strategies on social networks, in ACM Conference on Information & Knowledge Management, Canada, (2010), 1817–1820. https://doi.org/10.1145/1871437.1871737
    [15] L. Zhu, B. Wang, Stability analysis of a SAIR rumor spreading model with control strategies in online social networks, Inf. Sci., 526 (2020), 1–19. https://doi.org/10.1016/j.ins.2020.03.076 doi: 10.1016/j.ins.2020.03.076
    [16] Z. He, Z. Cai, J. Yu, X. Wang, Y. Sun, Y. Li, Cost-efficient strategies for restraining rumor spreading in mobile social networks, IEEE Trans. Veh. Technol., 66 (2017), 2789–2800. https://doi.org/10.1109/TVT.2016.2585591 doi: 10.1109/TVT.2016.2585591
    [17] L. A. Huo, Y. Q. Zhang, Effect of global and local refutation mechanism on rumor propagation in heterogeneous network, Mathematics, 10 (2022), 586. https://doi.org/10.3390/math10040586 doi: 10.3390/math10040586
    [18] Y. Zhang, J. Xu, M. Nekovee, Z. Li, The impact of official rumor-refutation information on the dynamics of rumor spread, Physica A, 607 (2022), 128096. https://doi.org/10.1016/j.physa.2022.128096 doi: 10.1016/j.physa.2022.128096
    [19] Y. Tian, X. Ding, Rumor spreading model with considering debunking behavior in emergencies, Appl. Math. Comput., 363 (2019), 124599. https://doi.org/10.1016/j.amc.2019.124599 doi: 10.1016/j.amc.2019.124599
    [20] H. Zhu, X. Zhang, Q. An, Global stability of a rumor spreading model with discontinuous control strategies, Physica A, 606 (2022), 128157. https://doi.org/10.1016/j.physa.2022.128157 doi: 10.1016/j.physa.2022.128157
    [21] A. Singh, Y. N. Singh, Nonlinear spread of rumor and inoculation strategies in the nodes with degree dependent tie strength in complex networks, Acta Phys. Pol. B, 44 (2013), 5–28. https://doi.org/10.5506/APhysPolB.44.5 doi: 10.5506/APhysPolB.44.5
    [22] Y. Cheng, L. Huo, L. Zhao, Stability analysis and optimal control of rumor spreading model under media coverage considering time delay and pulse vaccination, Chaos, Solitons Fractals, 157 (2022), 111931. https://doi.org/10.1016/j.chaos.2022.111931 doi: 10.1016/j.chaos.2022.111931
    [23] M. Jiang, Q. Gao, J. Zhuang, Reciprocal spreading and debunking processes of online misinformation: A new rumor spreading–debunking model with a case study, Physica A, 565 (2021), 125572. https://doi.org/10.1016/j.physa.2020.125572 doi: 10.1016/j.physa.2020.125572
    [24] L. Zhu, M. Zhou, Z. Zhang, Dynamical analysis and control strategies of rumor spreading models in both homogeneous and heterogeneous networks, J. Nonlinear Sci., 30 (2020), 2545–2576. https://doi.org/10.1007/s00332-020-09629-6 doi: 10.1007/s00332-020-09629-6
    [25] S Wen, J Jiang, Y Xiang, S. Yu, W. Zhou, W. Jia, To shut them up or to clarify: Restraining the spread of rumors in online social networks, IEEE Trans. Parallel Distrib. Syst., 25 (2014), 3306–3316. https://doi.org/10.1109/TPDS.2013.2297115 doi: 10.1109/TPDS.2013.2297115
    [26] K. Afassinou, Analysis of the impact of education rate on the rumor spreading mechanism, Physica A, 414 (2014), 43–52. https://doi.org/10.1016/j.physa.2014.07.041 doi: 10.1016/j.physa.2014.07.041
    [27] F. Fu, X. Chen, L. Liu, L. Wang, Social dilemmas in an online social network: the structure and evolution of cooperation, Phys. Lett. A, 371 (2007), 58–64. https://doi.org/10.1016/j.physleta.2007.05.116 doi: 10.1016/j.physleta.2007.05.116
    [28] F. Fu, L. Liu, L. Wang, Empirical analysis of online social networks in the age of Web 2.0, Physica A, 387 (2008), 675–684. https://doi.org/10.1016/j.physa.2007.10.006 doi: 10.1016/j.physa.2007.10.006
  • era-31-08-249 supplementary.rar
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(715) PDF downloads(77) Cited by(0)

Article outline

Figures and Tables

Figures(6)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog