Research article

Minimize the impact of rumors by optimizing the control of comments on the complex network

  • Received: 06 February 2021 Accepted: 26 March 2021 Published: 06 April 2021
  • MSC : 34H99

  • The rapid development of Internet and information technology has intensified the spread of rumors. Making full use of the comment mechanism on the Internet can effectively prevent the spread of rumors. This article focuses on strategies to reduce rumors by controlling comments. Firstly, based on the comment mechanism, a rumor propagation model with mixed rumor and truth is established. Secondly, we measure the cost of the rumor and, on this basis, model the comment based rumor-truth problem as the optimal control problem. Thirdly, we prove the existence of optimal control and derive the optimal system. Finally, the superiority of the optimal control strategy is verified by numerical simulation, and the rumor propagation is effectively slowed down under the premise of cost control, and the influence of some parameter changes on rumor cost-effectiveness control is studied.

    Citation: Ying Yu, Jiaomin Liu, Jiadong Ren, Qian Wang, Cuiyi Xiao. Minimize the impact of rumors by optimizing the control of comments on the complex network[J]. AIMS Mathematics, 2021, 6(6): 6140-6159. doi: 10.3934/math.2021360

    Related Papers:

  • The rapid development of Internet and information technology has intensified the spread of rumors. Making full use of the comment mechanism on the Internet can effectively prevent the spread of rumors. This article focuses on strategies to reduce rumors by controlling comments. Firstly, based on the comment mechanism, a rumor propagation model with mixed rumor and truth is established. Secondly, we measure the cost of the rumor and, on this basis, model the comment based rumor-truth problem as the optimal control problem. Thirdly, we prove the existence of optimal control and derive the optimal system. Finally, the superiority of the optimal control strategy is verified by numerical simulation, and the rumor propagation is effectively slowed down under the premise of cost control, and the influence of some parameter changes on rumor cost-effectiveness control is studied.



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    [1] J. Kostka, Y. A. Oswald, R. Wattenhofer, Word of mouth: Rumor dissemination in social networks, Springer Berlin Heidelberg, Berlin, Heidelberg, 2008.
    [2] W. Peterson, N. Gist, Rumor and public opinion, Am. J. Sociol., 57 (1951), 159-167. doi: 10.1086/220916
    [3] R. K. Garrett, Troubling consequences of online political rumoring, Hum. Commun. Res., 37 (2011), 255-274. doi: 10.1111/j.1468-2958.2010.01401.x
    [4] Y. Xiao, D. Chen, S. Wei, Q. Li, H. Wang, M. Xu, Rumor propagation dynamic model based on evolutionary game and anti-rumor, Nonlinear Dyn., 95 (2019), 523-539. doi: 10.1007/s11071-018-4579-1
    [5] Y. Xiao, W. Li, S. Qiang, Q. Li, Y. Liu, A rumor & anti-rumor propagation model based on data enhancement and evolutionary game, IEEE Trans. Emerging Top. Comput., 2020.
    [6] Y. Xiao, Q. Yang, C. Sang, Y. Liu, Rumor diffusion model based on representation learning and anti-rumor, IEEE Trans. Network Serv. Manage., 17 (2020), 1910-1923. doi: 10.1109/TNSM.2020.2994141
    [7] D. W. Huang, L. X. Yang, P. Li, X. Yang, Y. Y. Tang, Developing cost-effective rumor-refuting strategy through game-theoretic approach, IEEE Syst. J., (2020), 1-12.
    [8] T. Bian, X. Xiao, T. Xu, P. Zhao, W. Huang, Y. Rong, et al., Rumor detection on social media with bi-directional graph convolutional networks, Proc. AAAI Conf. Artif. Intell., 34 (2020), 549-556.
    [9] K. Yu, H. Jiang, T. Li, S. Han, X. Wu, Data fusion oriented graph convolution network model for rumor detection, IEEE Trans. Network Serv. Manage., 17 (2020), 2171-2181. doi: 10.1109/TNSM.2020.3033996
    [10] B. Wu, W. H. Cheng, Y. Zhang, J. Cao, J. Li, T. Mei, Unlocking author power: On the exploitation of auxiliary author-retweeter relations for predicting key retweeters, IEEE Trans. Knowledge Data Eng., 32 (2018), 549-559.
    [11] X. Luo, C. Jiang, W. Wang, Y. Xu, J. H. Wang, W. Zhao, User behavior prediction in social networks using weighted extreme learning machine with distribution optimization, Future Gener. Comput. Syst., 93 (2018), 1023-1035.
    [12] Q. Lv, Y. Wang, B. Zhang, Q. Jin, RV-ML: An effective rumor verification scheme based on multi-task learning model, IEEE Commun. Lett., 24 (2020), 2527-2531. doi: 10.1109/LCOMM.2020.3011714
    [13] Y. Zhang, J. Xu, A dynamic competition and predation model for rumor and rumor-refutation, IEEE Access, 9 (2021), 9117-9129. doi: 10.1109/ACCESS.2020.3047934
    [14] Y. Cheng, L. Huo, L. Zhao, Rumor spreading in complex networks under stochastic node activity, Phys. A: Stat. Mech. Appl., 559 (2020), 125061. doi: 10.1016/j.physa.2020.125061
    [15] L. Zhu, F. Yang, G. Guan, Z. Zhang, Modeling the dynamics of rumor diffusion over complex networks, Inf. Sci., 562 (2021), 240-258. doi: 10.1016/j.ins.2020.12.071
    [16] L. Huo, S. Chen, Rumor propagation model with consideration of scientific knowledge level and social reinforcement in heterogeneous network, Phys. A: Stat. Mech. Appl., 559 (2020), 125063. doi: 10.1016/j.physa.2020.125063
    [17] S. Yu, Z. Yu, H. Jiang, J. Li, Dynamical study and event-triggered impulsive control of rumor propagation model on heterogeneous social network incorporating delay, Chaos, Solitons Fract., 145 (2021), 110806. doi: 10.1016/j.chaos.2021.110806
    [18] D. Daley, D. Kendall, Epidemics and rumours, Nature, 204 (1964), 1118.
    [19] D. J. Daley, D. G. Kendall, Stochastic rumours, IMA J. Appl. Math., 1 (1965), 42-55.
    [20] D. H. Zanette, Dynamics of rumor propagation on small-world networks, Phys. Rev. E, 65 (2001), 041908.
    [21] D. H. Zanette, Critical behavior of propagation on small-world network, Phys. Rev. E, 64 (2001), 050901. doi: 10.1103/PhysRevE.64.050901
    [22] Y. Moreno, M. Nekovee, A. F. Pacheco, Dynamics of rumor spreading in complex networks, Phys. Rev. E, 69 (2004), 066130. doi: 10.1103/PhysRevE.69.066130
    [23] R. Pastor-Satorras, A. Vespignani, Epidemic dynamics and endemic states in complex networks, Phys. Rev. E, 63 (2001), 066117. doi: 10.1103/PhysRevE.63.066117
    [24] Y. Moreno, R. Pastor-Satorras, A. Vespignani, Epidemic outbreaks in complex heterogeneous networks, Eur. Phys. J. B-Condens. Matter, 26 (2002), 521-529.
    [25] M. Nekovee, Y. Moreno, G. Bianconi, M. Marsili, Theory of rumour spreading in complex social networks, Phys. A: Stat. Mech. Appl., 374 (2007), 457-470. doi: 10.1016/j.physa.2006.07.017
    [26] J. Wang, L. Zhao, R. Huang, 2SI2R rumor spreading model in homogeneous networks, Phys. A: Stat. Mech. Appl., 413 (2014), 153-161. doi: 10.1016/j.physa.2014.06.053
    [27] J. Zhou, Z. Liu, B. Li, Influence of network structure on rumor propagation, Phys. Lett. A, 368 (2007), 458-463. doi: 10.1016/j.physleta.2007.01.094
    [28] F. Roshani, Y. Naimi, Effects of degree-biased transmission rate and nonlinear infectivity on rumor spreading in complex social networks, Phys. Rev. E, 85 (2012), 036109. doi: 10.1103/PhysRevE.85.036109
    [29] L. Zhao, X. Qiu, X. Wang, J. Wang, Rumor spreading model considering forgetting and remembering mechanisms in inhomogeneous network, Phys. A: Stat. Mech. Appl., 392 (2013), 987-994. doi: 10.1016/j.physa.2012.10.031
    [30] Z. He, Z. Cai, X. Wang, Modeling propagation dynamics and developing optimized countermeasures for rumor spreading in online social networks, Int. Conf. Distrib. Comput. Syst., 2015 (2015), 205-214.
    [31] Q. Liu, T. Li, M. Sun, The analysis of an seir rumor propagation model on heterogeneous network, Phys. A: Stat. Mech. Appl., 469 (2017), 372-380. doi: 10.1016/j.physa.2016.11.067
    [32] W. Liu, T. Li, X. Cheng, H. Xu, X. Liu, Spreading dynamics of a cyber violence model on scale-free networks, Phys. A: Stat. Mech. Appl., 531 (2019), 121752. doi: 10.1016/j.physa.2019.121752
    [33] P. Van Mieghem, J. Omic, R. Kooij, Virus spread in networks, IEEE/ACM Trans. Networking, 17 (2008), 1-14.
    [34] P. Van Mieghem, The n-intertwined sis epidemic network model, Computing, 93 (2011), 147-169. doi: 10.1007/s00607-011-0155-y
    [35] F. D. Sahneh, F. N. Chowdhury, C. M. Scoglio, On the existence of a threshold for preventive behavioral responses to suppress epidemic spreading, Sci. Rep., 2 (2012), 632. doi: 10.1038/srep00632
    [36] S. Wen, J. Jiang, Y. Xiang, S. Yu, W. Zhou, W. Jia, To shut them up or to clarify: Restraining the spread of rumor in online social networks, IEEE Trans. Parallel Distrib. Syst., 25 (2014), 3306-3316. doi: 10.1109/TPDS.2013.2297115
    [37] L. X. Yang, P. Li, X. Yang, Y. Y. Tang, Security evaluation of the cyber networks under advanced persistent threats, IEEE Access, 5 (2017), 20111-20123. doi: 10.1109/ACCESS.2017.2757944
    [38] K. Huang, P. D. Li, L. X. Yang, X. F. Yang, Y. Y. Tang, Seeking best-balanced patch-injecting strategies through optimal control approach, Secur. Commun. Networks, 2019 (2019), 122019.
    [39] S. Xu, W. Lu, Z. Zhan, A stochastic model of multivirus dynamics, IEEE Trans. Depend. Secure Comput., 9 (2012), 30-45. doi: 10.1109/TDSC.2011.33
    [40] S. Xu, W. Lu, L. Xu, Z. Zhan, Adaptive epidemic dynamics in networks: Thresholds and control, Acm Trans. Auton. Adap. Syst., 8 (2014), 1-19.
    [41] L. Yang, M. Draief, X. Yang, Heterogeneous virus propagation in networks: A theoretical study, Math. Methods Appl. Sci., 40 (2017), 1396-1413. doi: 10.1002/mma.4061
    [42] L. X. Yang, T. R. Zhang, X. F. Yang, Y. B. Wu, Y. Yan, Effectiveness analysis of a mixed rumor-quelling strategy, J. Franklin Inst., 355 (2018), 8079-8105. doi: 10.1016/j.jfranklin.2018.07.040
    [43] C. Pan, L. Yang, X. Yang, Y. Wu, Y. Tang, An effective rumor-containing strategy, Phys. A: Stat. Mech. Appl., 500 (2018), 80-91. doi: 10.1016/j.physa.2018.02.025
    [44] J. Zhao, L. Yang, X. Zhong, X. Yang, Y. Wu, Y. Tang, Minimizing the impact of a rumor via isolation and conversion, Phys. A: Stat. Mech. Appl., 526 (2019), 120867. doi: 10.1016/j.physa.2019.04.103
    [45] E. M. Stein, R. Shakarchi, Real analysis: Measure theory, integration, and Hilbert spaces, Princeton University Press, 2005.
    [46] D. Liberzon, Calculus of variations and optimal control theory: A concise introduction, Princeton University Press, 2012.
    [47] R. C. Robinson, An introduction to dynamical systems: Continuous and discrete, American Mathematical Society: Providence, RI, USA, 2004.
    [48] S. Lenhart, J. T. Workman, Optimal control applied to biological models, Champion and Hall/CRC, 2007.
    [49] S. Jana, T. K. Kar, A mathematical study of a prey-predator model in relevance to pest control, Nonlinear Dyn., 74 (2013), 667-683. doi: 10.1007/s11071-013-0996-3
    [50] Y. Lan, Z. Lian, R. Zeng, D. Zhu, Y. Xia, M. Liu, et al., A statistical model of the impact of online rumors on theinformation quantity of online public opinion, Phys. A: Stat. Mech. Appl., 541 (2020), 123623. doi: 10.1016/j.physa.2019.123623
    [51] J. Chen, L. Yang, X. Yang, Y. Tang, Cost-effective anti-rumor message-pushing schemes, Phys. A: Stat. Mech. Appl., 540 (2020), 123085. doi: 10.1016/j.physa.2019.123085
    [52] R. Albert, A. L. Barabási, Statistical mechanics of complex networks, Rev. Modern Phys., 74 (2002), 47. doi: 10.1103/RevModPhys.74.47
    [53] D. J. Watts, S. H. Strogatz, Collective dynamics of 'small-world' networks, Nature, 393 (1998), 440-442. doi: 10.1038/30918
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