Chinese Journal of Management Science >
2025 , Vol. 33 >Issue 6: 140 - 150
DOI: https://doi.org/10.16381/j.cnki.issn1003-207x.2022.1662
Research on the Timing of Online Public Opinion Intervention Considering the Psychological Factors of Netizens
Received date: 2022-07-27
Revised date: 2023-02-24
Online published: 2025-07-04
The timing of online public opinion intervention is crucial for the government in maintaining its public image, ensuring social stability, and gaining public trust. Existing research provides references for the government's control over the timing of intervention in online public opinion. However, in today's complex online environment, the internal factors among netizens cannot be ignored when considering their impact on the spread of online public opinion, especially their psychological factors. The SEIR model is built, taking into account the role of netizens' psychology in determining the timing of online public opinion intervention. It introduces a psychological tolerance parameter and investigates the impact of government intervention timing on the spread of public opinion. Through simulation experiments, it simulates the changes in the spread status of online public opinion in a scale-free network under different government intervention timings and different levels of psychological tolerance. The simulation results suggest that the timing of online public opinion intervention is not necessarily “the earlier, the better,” and the optimal intervention timing should be selected with consideration of psychological tolerance. Additionally, public opinion data are collected hourly during the outbreak periods of two events: “The student's fatal fall at Chengdu No. 49 Middle School” and “The destruction of the protective forest in Dunhuang's thousands of acres of desert.” It uses these case studies to validate the accuracy of the model through simulation. The limitations of the “fixed transfer probability” assumption in classical dynamics of communication is addressed and the impact of netizens' psychological factors on the effectiveness of government intervention is described by setting relevant mechanisms. The research findings hold significant importance for relevant authorities in conducting scientifically and reasonably governed online public opinion management.
Mingzhu Wang , Linjiang Guo , Yijun Liu . Research on the Timing of Online Public Opinion Intervention Considering the Psychological Factors of Netizens[J]. Chinese Journal of Management Science, 2025 , 33(6) : 140 -150 . DOI: 10.16381/j.cnki.issn1003-207x.2022.1662
1 | 中国互联网信息中心. 第52 次《中国互联网络发展状况统计报告》[EB/OL]. (2023-08-28)[2023-10-02]. . |
China Internet Network Information Center. The 52nd “Statistical Report on Internet Development in China”[EB/OL]. (2023-08-28) [2023-10-02]. . | |
2 | Goffman W, Newill V A. Generalization of epidemic theory. An application to the transmission of IDEAS[J]. Nature, 1964,204:225-228. |
3 | Kermack W O, McKendrick A G. Contributions to the mathematical theory of epidemics II:The problem of endemicity[J]. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 1932, 138(834): 55-83. |
4 | Kermack W O, McKendrick A G. Contributions to the mathematical theory of epidemics-I. 1927[J]. Bulletin of Mathematical Biology, 1991, 53(1-2): 33-55. |
5 | Escalante R, Odehnal M. A deterministic mathematical model for the spread of two rumors[J]. Afrika Matematika, 2020, 31(2): 315-331. |
6 | Wan C, Li T, Sun Z. Global stability of a SEIR rumor spreading model with demographics on scale-free networks[J]. Advances in Difference Equations, 2017, 2017(1): 253. |
7 | Daley D J, Kendall D G. Epidemics and rumours[J]. Nature, 1964, 204(4963): 1118. |
8 | Maki, D P, Thompson M.Mathematical models and applications: With emphasis on the social, life, and management sciences[M].New Jersey: Prentice Hall, 1973. |
9 | Sudbury A. The proportion of the population never hearing a rumour[J]. Journal of Applied Probability, 1985, 22(2): 443-446. |
10 | Belen S, Kropat E, Weber G W. On the classical Maki-Thompson rumour model in continuous time[J]. Central European Journal of Operations Research, 2011, 19(1): 1-17. |
11 | 祁凯,杨志.突发危机事件网络舆情治理的多情景演化博弈分析[J].中国管理科学,2020,28(3):59-70. |
Qi K, Yang Z. Multi-scenario evolutionary game analysis of network public opinion governance in sudden crisis[J].Chinese Journal of Management Science,2020,28(3):59-70 | |
12 | 王治莹,李勇建.政府干预下突发事件舆情传播规律与控制决策[J].管理科学学报,2017,20(2):43-52+62. |
Wang Z Y, Li J Y. Propagation law and coping strategies for public opinions in emergency withthe consideration of the government intervention[J].Journal of Management Sciences in China,2017,20(2):43-52+62. | |
13 | 王治莹,王伟康,岳朝龙.政府干预下多种舆情信息交互传播模型与仿真[J].系统仿真学报,2020,32(5):956-966. |
Wang Z Y, Wang W K, Yue C L. Model and simulation of interactive dissemination of multiple public opinion information under government intervention[J].Journal of System Simulation,2020,32(5):956-966. | |
14 | Chen H L, Chen B, Ai C, et al. Research on rumor propagation simulation based on behavior-attribute[C]//Preceedings of the 2020 IEEE Fifth International Conference on Data Science in Cyberspace (DSC),Hong Kong, China,July 27-29, IEEE, 2020: 225-231. |
15 | 项权,于同洋,肖人彬.突发事件网络舆情演化与干预[J].计算机应用,2018,38(S2):97-102. |
Xiang Q, Yu T Y, Xiao R B. Evolution and intervention of public opinion in emergencies[J].Journal of Computer Applications,2018,38(S2):97-102. | |
16 | 谢卫红,杨超波,朱郁筱.食品安全网络舆情的重复感染SIR模型研究[J].系统工程学报,2022,37(2):145-160. |
Xie W H, Yang C B, Zhu Y X. Research on repeated infection SIR model of network public opinionabout food safety[J].Journal of Systems Engineering,2022,37(2):145-160. | |
17 | 陈帅.基于多层耦合网络的舆情传播控制研究[J].系统仿真学报,2020,32(12):2353-2361. |
Chen S. Research on dissemination and control of public opinion based on multilayer coupled network[J].Journal of System Simulation,2020,32(12):2353-2361. | |
18 | Wang Y, Qing F, Yan M. Dynamics of 2SIH2R rumor-spreading model in a heterogeneous network[J]. Wireless Communications and Mobile Computing, 2022, 2022(1):7398387. |
19 | Knapp R H. A psychology of rumor[J]. Public Opinion Quarterly, 1944, 8(1): 22-37. |
20 | 迟钰雪,刘怡君.逆反心理的网络舆情传播机制研究[J].系统工程学报,2019,34(5):610-620. |
Chi Y X, Liu Y J. Study on the transmission mechanism of online public opinion of reverse psychology[J].Journal of Systems Engineering,2019,34(5):610-620. | |
21 | 黄远,刘怡君.多层多属性舆情传播网络的仿真研究[J].系统工程学报,2019,34(6):844-854. |
Huang Y, Liu Y J. Simulation research on propagation network with multi-layer and multi-attribute public opinions[J].Journal of Systems Engineering,2019,34(6):844-854. | |
22 | Cheng Y Y, Huo L A, Ma L, et al. Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading model[J]. International Journal of Modern Physics C, 2020, 31(2): 2050034. |
23 | Xu H, Li T, Liu X D, et al. Spreading dynamics of an online social rumor model with psychological factors on scale-free networks[J].Physica A: Statistical Mechanics and Its Applications, 2019, 525: 234-246. |
24 | Zhao L J, Qiu X Y, Wang X L, et al. Rumor spreading model considering forgetting and remembering mechanisms in inhomogeneous networks[J]. Physica A: Statistical Mechanics and Its Applications, 2013, 392(4): 987-994. |
25 | Tian R Y, Zhang X F, Liu Y J. SSIC model: A multi-layer model for intervention of online rumors spreading[J]. Physica A: Statistical Mechanics and Its Applications, 2015, 427: 181-191. |
26 | Huo L A, Ma C Y. Optimal control of rumor spreading model with consideration of psychological factors and time delay[J]. Discrete Dynamics in Nature and Society, 2018, 2018(1):9314907. |
27 | Jain A, Dhar J, Gupta V. Rumor model on homogeneous social network incorporating delay in expert intervention and government action[J]. Communications in Nonlinear Science and Numerical Simulation, 2020, 84: 105189. |
28 | 王楠,肖敏,蒋海军,等.时滞和扩散影响下社交网络谣言传播动力学[J].物理学报,2022,71(18):7-17. |
Wang N, Xiao M, Jiang H J,et al. Rumor propagation dynamics in social networks under the influence of time delay and diffusion[J].Acta Physica Sinica,,2022,71(18):7-17. | |
29 | Qiu X Y, Zhao L J, Wang J J, et al. Effects of time-dependent diffusion behaviors on the rumor spreading in social networks[J]. Physics Letters A, 2016, 380(24): 2054-2063. |
30 | Wang B, Chen G, Fu L Y, et al. Drimux: Dynamic rumor influence minimization with user experience in social networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2017, 29(10): 2168-2181. |
31 | Alshahrani M, Fuxi Z, Sameh A, et al. “Top-k influential users selection based on combined katz centrality and propagation probability”[C]//Proceedings of the 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA),Chengdu,China,April 20-22, IEEE, 2018:52-56. |
32 | Anderson R M, May R M. Infectious diseases of humans: Dynamics and control[M].Oxford:Oxford University Press, 1992. |
33 | Liu X D, Li T, Tian M. Rumor spreading of a SEIR model in complex social networks with hesitating mechanism[J]. Advances in Difference Equations, 2018, 2018(1): 1-24. |
34 | Dong X F, Liu Y J, Wu C, et al. A double-identity rumor spreading model[J]. Physica A: Statistical Mechanics and Its Applications, 2019, 528: 121479. |
35 | Xu J H, Zhang L, Ma B J, et al. Impacts of suppressing guide on information spreading[J]. Physica A: Statistical Mechanics and Its Applications, 2016, 444: 922-927. |
36 | 朱宏淼,闫辛,齐佳音,等.社会民众新冠病毒疫苗接种意识传播模型与干预策略研究[J].中国管理科学: 2023,31(8):269-277. |
Zhu H M, Yan X, Qi J Y,et al. Research on communication model and intervention strategy of COVID-19 vaccination consciousness among public[J].Chinese Journal of Management Science,2023,31(8):269-277. | |
37 | 崔金栋,陈思远,李晨雨.基于大数据的多类型网络谣言类型平息方式实证研究——以“新冠肺炎疫情期间谣言”为例[J].情报理论与实践,2021,44(4):67-73. |
Cui J D, Chen S Y, Li C Y. An empirical study on the ways to quit multi-types of internet rumors based on big data: Take “rumors during the novel coronavirus pneumonia epidemic” as an example[J].Information Studies:Theory & Application,2021,44(4):67-73. | |
38 | 李仕争,丁菊玲,蒋鹏,等.移动社交网络谣言演化的系统动力学模型与仿真[J].情报杂志,2016,35(9):117-123+103. |
Li S Z, Ding J L, Jiang P,et al. System dynamics model and simulation of internet rumors for mobile social network[J].Journal of Intelligence,2016,35(9):117-123+103. | |
39 | 林伟鹏,冯保艺.管理学领域的曲线效应及统计检验方法[J].南开管理评论,2022,25(1):155-166. |
Lin W P, Feng B Y. Curvilinear effect and statistical test method in the management research[J].Nankai Business Review,2022,25(1):155-166. | |
40 | 吴伟炯.破解“通勤悖论”:通勤时间如何影响幸福感[J].心理学报,2017,49(11):1449-1459. |
Wu W J. Resolving “Commuting Paradox”: How commute time influences subjective well-being[J].Acta Psychologica Sinica,2017,49(11):1449-1459. | |
41 | 王红兵,王光辉.社会事件网络舆情的政府干预机制[J].中国科学院院刊,2015,30(1):97-104. |
Wang H B, Wang G H.Government intervention mechanism of social public opinion crisis[J].Bulletin of Chinese Academy of Sciences,2015,30(1):97-104. | |
42 | Dong S, Deng Y B, Huang Y C. SEIR model of rumor spreading in online social network with varying total population size[J]. Communications in Theoretical Physics, 2017, 68(4): 545-552. |
43 | Li, Y, Qian M J, Jin D P, et al. Revealing the efficiency of information diffssion in online social networks of microblog[J]. Information Sciences, 2015, 293: 383-389. |
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