新冠疫情下的SEIRD時滯性謠言傳播模型及辟謠策略

唐梁鴻緒; 王衛蘋; 王昊; 員曼曼; 羅熊; 李建武

doi:10.13374/j.issn2095-9389.2021.03.16.005

新冠疫情下的SEIRD時滯性謠言傳播模型及辟謠策略

doi: 10.13374/j.issn2095-9389.2021.03.16.005

唐梁鴻緒¹,
王衛蘋^{1, 2, 3, ,},
王昊⁴,
員曼曼^{1, 2, 3},
羅熊^{1, 2, 3},
李建武^{5, 6}

1.
北京科技大學計算機與通信工程學院，北京 100083
2.
北京科技大學順德研究生院，佛山 528399
3.
材料領域知識工程北京市重點實驗室，北京 100083
4.
中國信息通信研究院信息化與工業化融合研究所，北京 100191
5.
北京理工大學前沿技術研究院，濟南 250300
6.
黃河科技學院工學部，鄭州 450000

基金項目: 國家自然科學基金資助項目（81961138010, U1836106）; 中央高校基本科研業務費資助項目（FRF-TP-19-005A3）；北京科技大學順德研究生院科技創新基金資助項目（BK19BF006，BK20BF010）

詳細信息

通訊作者:
E-mail: weipingwangjt@ustb.edu.cn

中圖分類號: TN915.08
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- 文章訪問數: 1518
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- 被引次數: 0
出版歷程
- 收稿日期: 2021-03-16
- 網絡出版日期: 2022-03-11
- 刊出日期: 2022-06-25

Time-lag rumor propagation model and rumor-refuting strategy of SEIRD under COVID-19

TANG Liang-hong-xu¹,
WANG Wei-ping^{1, 2, 3
, ,},
WANG Hao⁴,
YUAN Man-man^{1, 2, 3},
LUO Xiong^{1, 2, 3},
LI Jian-wu^{5, 6}

1.
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
2.
Shunde Graduate School, University of Science and Technology Beijing, Foshan 528399, China
3.
Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083, China
4.
The Research Institute of Informatization and Industrialization Integration, China Academy of Information and Communications Technology, Beijing 100191, China
5.
Advanced Technology Research Institute, Beijing Institute of Technology, Jinan 250300, China
6.
Faculty of Engineering, Huanghe Science and Technology College, Zhengzhou 450000, China

More Information

Corresponding author: E-mail: weipingwangjt@ustb.edu.cn

摘要

摘要: 隨著互聯網的發展與新冠疫情的蔓延，疫情相關謠言的流量與受關注度大大提高，使其能夠迅速發酵并造成極其不良的社會影響。由此可見，研究網絡謠言的傳播過程并給出遏制網絡謠言傳播的策略有著重大意義。在傳統網絡謠言傳播SIR(Susceptible, infected, recovered)模型的基礎上加入潛在信謠者與鐵桿信謠者群體，引入政府辟謠機制，同時考慮辟謠者與政府辟謠的滯后性以及高等教育普及率對謠言傳播及辟謠過程的影響，建立了SEIRD(Susceptible, exposed, infected, recovered, die-hard-infected)謠言傳播模型，以研究一個網絡謠言自誕生起，不知情者、潛在信謠者、信謠者、鐵桿信謠者以及醒悟者這五類網民比例在有無政府辟謠、辟謠是否具有滯后性、以及網民不同比例高等教育率下的變化規律，并通過實驗仿真驗證了模型的有效性，為控制網絡輿情傳播提供參考。此外，還提出了用于衡量辟謠者群體及政府權威機構辟謠能力的辟謠系數。研究結果表明，提高高等教育普及率對于減緩謠言傳播、降低謠言傳播峰值有著顯著效果；政府權威機構辟謠對于最終徹底消滅謠言起決定性作用；消滅辟謠的滯后性對于減緩網絡謠言傳播同樣有極大幫助。為此，還提出了一種未來可能的消滅辟謠滯后性的網絡謠言抑制策略。
- 網絡謠言 /
- 謠言傳播模型 /
- 鐵桿信謠者 /
- 時滯性 /
- 權威辟謠 /
- 高等教育普及率 /
- 辟謠系數 /
- 辟謠策略
Abstract: With the increasing popularity of the Internet and the spread of COVID-19, epidemic-related rumors have attracted significant attention, allowing them to brew quickly and pose extremely negative social impacts. It is of great significance to investigate the propagation process of online rumors and offer tentative strategies to curb it. Based on the traditional susceptible, infected, recovered (SIR) model of online rumor propagation, groups of potential and die-hard rumor believers were introduced in this paper, establishing an authoritative rumor-refuting mechanism. Meanwhile, this paper considered factors such as the time-lag effect of rumor refutation from the nonauthoritative and authoritative institutions and the impact of the popularizing rate of higher education on the propagation and refutation of rumors. As a result of the process, the SEIRD (susceptible, exposed, infected, recovered, die-hard-infected) rumor propagation model was established to study how the proportion of the susceptible, exposed, infected, recovered, and die-hard-infected varies under different popularizing rates of higher education, the presence or absence of the authoritative rumor-refuting institutions, and the time-lag effect of rumor refutation. Finally, the model’s effectiveness was verified via experimental simulation, which provided a reference for controlling the spread of online rumor propagation. In addition, the paper proposed a rumor-refuting coefficient to measure the rumor-refuting ability of the nonauthoritative and authoritative institutions. The results show that (1) increasing popularizing rate of higher education significantly slows down the rumor propagation and reduces the rumor propagation peak; (2) refuting the rumors based on the authoritative institutions is decisive for the ultimate elimination of rumors; and (3) eliminating the time-lag effect in refuting rumors facilitates slowing down the propagation of the online rumors. Therefore, the paper puts forward a feasible strategy to eliminate the time-lag effect of online rumor refutation in the future.
- online rumor /
- rumor propagation model /
- die-hard infected believer /
- time-lag effect /
- authoritative rumor refutation /
- popularizing rate of higher education /
- rumor-refuting coefficient /
- rumor-refuting strategy

HTML全文

圖 1 SEIRD網絡謠言傳播模型流程圖

Figure 1. Flow chart of the SEIRD propagation model

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圖 2 SEIRD小型群體網絡謠言傳播模型

Figure 2. SEIRD small group online rumor propagation model

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圖 3 普及高等教育和權威機構對我國網絡環境下謠言傳播的影響。（a）SEIRD我國網絡謠言傳播模型；（b）引入權威機構辟謠的SEIRD我國網絡謠言傳播模型；（c）提高高等教育普及率的SEIRD我國網絡謠言傳播模型；（d）同時提高高等教育普及率并引入權威機構辟謠的SEIRD我國網絡謠言傳播模型

Figure 3. Influence of popularized higher education and authoritative institutions on rumor propagation in China’s online environment: (a) China’s SEIRD online rumor propagation model; (b) China’s SEIRD authoritative rumor-refuting model; (c) China’s SEIRD model for increasing the popularizing rate of higher education; (d) China’s SEIRD model for both authoritative rumor-refuting and increasing the popularizing rate of higher education

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圖 4 不同高等教育普及率對最終醒悟者與鐵桿信謠者群體占網民總人口比例的影響

Figure 4. Influence of different higher education popularizing rates on the proportion of the exposed and die-hard-infected in the total population of internet users

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圖 5 考慮“權威機構無滯后性辟謠并且普及高等教育”的SEIRD網絡謠言傳播模型

Figure 5. SEIRD model considering the authoritative rumor refutation without time lag and popularizing rate of the higher education

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圖 6 權威機構辟謠對雙黃連事件謠言傳播的影響。（a）無權威機構辟謠下的雙黃連事件謠言傳播模型；（b）有權威機構辟謠下的雙黃連事件謠言傳播模型

Figure 6. Influence of authoritative rumor refutation on the rumor spread of the Shuanghuanglian incident: (a) SEIRD rumor propagation model of the Shuanghuanglian incident without authoritative rumor refutation; (b) SEIRD rumor propagation model of Shuanghuanglian incident with authoritative rumor refutation

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參考文獻(32)

[1]	Liu F, Li M T. Research on SIRI rumor spreading model with spontaneous behavior. J Syst Sci Math Sci, 2020, 40(7): 1257 doi: 10.12341/jssms13922 劉芳, 李明濤. 一類具有自發行為的SIRI謠言傳播模型研究. 系統科學與數學, 2020, 40(7):1257 doi: 10.12341/jssms13922
[2]	Ding X J, Li L X. The spreading dynamics of rumors in social media under the anti-silence spiral effect. Syst Eng Theory Pract, 2020, 40(12): 3149 doi: 10.12011/SETP2019-1700 丁學君, 李臨霄. 反沉默螺旋效應下社交媒體謠言傳播動力學研究. 系統工程理論與實踐, 2020, 40(12):3149 doi: 10.12011/SETP2019-1700
[3]	Fu W, Pan X Z, Liu Y Z. Rumor spreading model based on principle of social identity. Comput Eng, 2018, 44(9): 136 付偉, 潘曉中, 劉亞州. 基于社會認同原理的謠言擴散模型. 計算機工程, 2018, 44(9):136
[4]	Hosni A I E, Li K, Ahmad S. Minimizing rumor influence in multiplex online social networks based on human individual and social behaviors. Inf Sci, 2020, 512: 1458 doi: 10.1016/j.ins.2019.10.063
[5]	Wang X L, Zhao L J, Xie W L. Rumor spreading model with variable forgetting rate in scale-free network. Syst Eng Theory Pract, 2015, 35(2): 458 doi: 10.12011/1000-6788(2015)2-458 王筱莉, 趙來軍, 謝婉林. 無標度網絡中遺忘率變化的謠言傳播模型研究. 系統工程理論與實踐, 2015, 35(2):458 doi: 10.12011/1000-6788(2015)2-458
[6]	Zhang J P, Guo H M, Jing W J, et al. Dynamic analysis of rumor propagation model based on true information spreader. Acta Phys Sin, 2019, 68(15): 150501 doi: 10.7498/aps.68.20190191 張菊平, 郭昊明, 荊文君, 等. 基于真實信息傳播者的謠言傳播模型的動力學分析. 物理學報, 2019, 68(15):150501 doi: 10.7498/aps.68.20190191
[7]	Fan C L, Song H M, Ding G H. Research on an improved SEIR network rumor propagation model. J Intell, 2017, 36(3): 86 doi: 10.3969/j.issn.1002-1965.2017.03.015 范純龍, 宋會敏, 丁國輝. 一種改進的SEIR網絡謠言傳播模型研究. 情報雜志, 2017, 36(3):86 doi: 10.3969/j.issn.1002-1965.2017.03.015
[8]	Liu J Y, Li D P. Research on edge immunization strategy of online social network based on triple group structure. Comput Eng, 2018, 44(6): 130 doi: 10.3969/j.issn.1000-3428.2018.06.023 劉建友, 李代平. 基于三元組結構的在線社交網絡邊免疫策略研究. 計算機工程, 2018, 44(6):130 doi: 10.3969/j.issn.1000-3428.2018.06.023
[9]	Luo J Y, Tang N J. Rumor propagation model based on edge-based compartmental theory. J Comput Appl, 2019, 39(11): 3409 羅靖宇, 唐寧九. 基于邊劃分理論的謠言傳播模型. 計算機應用, 2019, 39(11):3409
[10]	Qiu L Q, Liu S Q. C-SIW rumor propagation model with variable propagation rate and perception mechanism in social networks. Discrete Dyn Nat Soc, 2020: 5712968
[11]	Wang J J, Jiang Z A, Deng Y F, et al. Modeling and influence factors of warning dissemination. J Univ Sci Technol Beijing, 2012, 34(12): 1453 王晶晶, 蔣仲安, 鄧云峰, 等. 警報傳播過程建模及影響因素. 北京科技大學學報, 2012, 34(12):1453
[12]	Zhang Y H, Zhu J J. Dynamic behavior of an I2S2R rumor propagation model on weighted contract networks. Phys A:Stat Mech Appl, 2019, 536: 120981 doi: 10.1016/j.physa.2019.04.217
[13]	Chen S S, Jiang H J, Li L, et al. Dynamical behaviors and optimal control of rumor propagation model with saturation incidence on heterogeneous networks. Chaos Solitons Fractals, 2020, 140: 110206 doi: 10.1016/j.chaos.2020.110206
[14]	Zhu L H, Liu M X, Li Y M. The dynamics analysis of a rumor propagation model in online social networks. Phys A:Stat Mech Appl, 2019, 520: 118 doi: 10.1016/j.physa.2019.01.013
[15]	Dong S, Huang Y C. A class of rumor spreading models with population dynamics. Commun Theor Phys, 2018, 70(6): 795 doi: 10.1088/0253-6102/70/6/795
[16]	Tan Z H, Shi Y C, Shi N X, et al. Rumor propagation analysis model inspired by gravity theory for online social networks. J Comput Res Dev, 2017, 54(11): 2586 doi: 10.7544/issn1000-1239.2017.20160434 譚振華, 時迎成, 石楠翔, 等. 基于引力學的在線社交網絡空間謠言傳播分析模型. 計算機研究與發展, 2017, 54(11):2586 doi: 10.7544/issn1000-1239.2017.20160434
[17]	Wei Y, Yin Y J. Rumor propagation model for crowd-gathered place of emergency event. Comput Eng, 2019, 45(9): 302 蔚瑩, 殷雁君. 突發事件人群聚集場所的謠言傳播模型. 計算機工程, 2019, 45(9):302
[18]	Zhao M, Chen W X, Song Q K. Research on a rumor spreading model with media coverage. Appl Math Mech, 2018, 39(12): 1400 趙敏, 陳文霞, 宋乾坤. 考慮媒體報道效應的謠言傳播模型研究. 應用數學和力學, 2018, 39(12):1400
[19]	Zhu L H, Li L. Dynamic analysis of rumor-spread-delaying model based on rumor-refuting mechanism. Acta Phys Sin, 2020, 69(2): 020501 doi: 10.7498/aps.69.20191503 朱霖河, 李玲. 基于辟謠機制的時滯謠言傳播模型的動力學分析. 物理學報, 2020, 69(2):020501 doi: 10.7498/aps.69.20191503
[20]	Zhu L H, Liu W S, Zhang Z D. Delay differential equations modeling of rumor propagation in both homogeneous and heterogeneous networks with a forced silence function. Appl Math Comput, 2020, 370: 124925
[21]	Li C R. A study on time-delay rumor propagation model with saturated control function. Adv Differ Equ, 2017, 2017(1): 1 doi: 10.1186/s13662-016-1057-2
[22]	Zhu L H, Zhao H Y, Wang H Y. Stability and spatial patterns of an epidemic-like rumor propagation model with diffusions. Phys Scr, 2019, 94(8): 085007 doi: 10.1088/1402-4896/ab1568
[23]	Zhu L H, Zhao H Y, Wang H Y. Partial differential equation modeling of rumor propagation in complex networks with higher order of organization. Chaos:Interdiscip J Nonlinear Sci, 2019, 29(5): 053106 doi: 10.1063/1.5090268
[24]	Zhang J X, Wang L T, Zhang J H. Internet rumors spreading and control model with multiple propagation sources. Inf Sci, 2020, 38(11): 115 張金鑫, 王麗婷, 張金華. 具有多個傳播源的網絡謠言傳播與導控模型研究. 情報科學, 2020, 38(11):115
[25]	Chen A, Wang Z J, Chen Y H. Spread and governance of pseudo-science Internet rumors in major public healthy emergencies based on SEIR model: A case study of COVID-19 epidemic. Sci Technol Rev, 2020, 38(4): 55 doi: 10.3981/j.issn.1000-7857.2020.04.007 陳安, 王子君, 陳櫻花. 基于SEIR模型視角的重大公共衛生事件中偽科學網絡謠言的傳播治理: 以新冠肺炎疫情為例. 科技導報, 2020, 38(4):55 doi: 10.3981/j.issn.1000-7857.2020.04.007
[26]	Huo L G, Chen S J. Rumor propagation model with consideration of scientific knowledge level and social reinforcement in heterogeneous network. Phys A:Stat Mech Appl, 2020, 559: 125063 doi: 10.1016/j.physa.2020.125063
[27]	Shi X X, Ye H P. Establishment and dynamic analysis of a stochastic SIRS rumor propagation model. J Donghua Univ (Nat Sci), 2020, 46(5): 828 石星星, 葉海平. 隨機謠言傳播模型的建立與動態分析. 東華大學學報(自然科學版), 2020, 46(5):828
[28]	Wang Q Y, Liu R R, Jia C X. Influence of opinion dynamics on rumor propagation in complex networks. Acta Phys Sin, 2021, 70(6): 351 王祁月, 劉潤然, 賈春曉. 復雜網絡上的意見動力學對謠言傳播的影響. 物理學報, 2021, 70(6):351
[29]	Wan Y P, Zhang D G, Ren Q H. Propagation and inhibition of online rumor with considering rumor elimination process. Acta Phys Sin, 2015, 64(24): 240501 doi: 10.7498/aps.64.240501 萬貽平, 張東戈, 任清輝. 考慮謠言清除過程的網絡謠言傳播與抑制. 物理學報, 2015, 64(24):240501 doi: 10.7498/aps.64.240501
[30]	Cao W B, Wu Z F, Yang T, et al. Entity and attribute extraction of terrorism event based on text corpus. Chin J Eng, 2020, 42(04): 500 曹文斌, 武卓峰, 楊濤, 等. 基于文本語料的涉恐事件實體屬性抽取. 工程科學學報, 2020, 42(04):500
[31]	Zheng H Y, Liao C L, Li T Z. A topic detection method for network long text. Chin J Eng, 2019, 41(9): 1208 鄭恒毅, 廖城霖, 李天柱. 一種面向網絡長文本的話題檢測方法. 工程科學學報, 2019, 41(9):1208
[32]	Office of the Central Cyberspace Affairs Commission, Cyberspace Administration of China. The 46th China Statistical Report on Internet Development[R/OL]. China Internet Network Information Center (2020-09-29) [2021-03-16]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202009/P020210205509651950014.pdf 中共中央網絡安全和信息化委員會辦公室, 中華人民共和國國家互聯網信息辦公室. 第46次中國互聯網絡發展狀況統計報告[R/OL]. 中國互聯網絡信息中心 (2020-09-29) [2021-03-16]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202009/P020210205509651950014.pdf