基于超网络的舆论演化动态模型

doi:10.13306/j.1672-3813.2021.02.004

复杂系统与复杂性科学

2021, Vol. 18

Issue (2): 29-38 DOI: 10.13306/j.1672-3813.2021.02.004

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基于超网络的舆论演化动态模型

王志平, 王佳

大连海事大学理学院,辽宁大连 116034

Dynamic Model of Public Opinion Evolution Based on Hyper-network

WANG Zhiping, WANG Jia

College of Science, Dalian Maritime University, Dalian 116034, China

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摘要针对舆论演化过程中的复杂动力学问题,提出了超网络视觉下的舆论演化动态模型,该模型包括节点的添加、重新连接链路、超边的添加以及节点的老化4个过程,其中节点代表关键词,超边代表关键词所构成的话题。其次,利用非均匀网络的演化机制,分别对该动态演化模型的超度、节点自身关注度与节点间影响力两个因素的超度进行了详细的理论分析,分析结果表明节点超度完全符合幂律分布。最后,通过Matlab仿真模拟,分析了不同参数对节点超度分布变化的影响,并进一步验证了结果是遵循幂律分布的。

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关键词 ：舆论, 超网络, 非均匀网络, 幂律分布, 动态演化机制

Abstract：Aiming at the complex dynamics problem in the evolution process of public opinion, this paper proposes a dynamic evolution model of public opinion under the vision of hyper-network. The model includes four processes: nodes addition, reconnection link, hyperedges addition and nodes aging, where node represents keywords and hyperedge represents topic of keywords. Secondly, by using the evolution mechanism of non-uniform network, a detailed theoretical analysis is carried out on the deviation of the dynamic evolution model, the deviation of the attention of nodes itself and the influence between nodes. The analysis results show that the deviation of nodes fully conforms to the power law distribution.Finally,the influence of different parameters on the variation of the node hyperdegree distribution is analyzed by MATLAB simulation, and the result is further verified to be power law distribution.

Key words： public opinion hyper-network non-uniform network power distribution dynamic evolution mechanism

收稿日期: 2020-08-09 出版日期: 2021-05-10

ZTFLH:	O175.6
	N941.3

基金资助:中央高校基本科研业务费重点科研培育项目(3132019323)

作者简介: 王志平(1964-),男,湖北鄂州人,博士,教授,主要研究方向为超网络理论与应用。

引用本文:

王志平, 王佳. 基于超网络的舆论演化动态模型[J]. 复杂系统与复杂性科学, 2021, 18(2): 29-38.
WANG Zhiping, WANG Jia. Dynamic Model of Public Opinion Evolution Based on Hyper-network. Complex Systems and Complexity Science, 2021, 18(2): 29-38.

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http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2021.02.004 或 http://fzkx.qdu.edu.cn/CN/Y2021/V18/I2/29

[1]刘泉, 荣莉莉, 颜克胜. 考虑媒体效应的微博网络热点事件舆论演化模型[J]. 系统工程学报, 2018,33(5): 577-588.
Liu Quan, Rong Lili, Yan Kesheng. Public opinion evolution model of hot events on weibo considering media effect [J]. Journal of Systems Engineering, 2018,33(5): 577-588.
[2]昂娟. 突发事件生命周期网络舆论演化及引导研究——以“魏则西事件”和“雷洋事件”为例[J]. 大理大学学报, 2018,3(5): 56-60.
Ang Juan. Study on the Evolution and guidance of network public opinion in emergency life cycle:a case study of “Wei Zexi Incident” and “Lei Yang Incident” [J]. Journal of Dali University, 2018,3(5): 56-60.
[3]French J R. A formal theory of social power[J]. Psychological Review, 1956,63(3): 181-194.
[4]Lehrer, K, Wagner C. Rational Consensus in Science and Society: A Philosophical and Mathematical Study[M]. Landon: Reidel, 1981,165.
[5]Wołoszyn M, Stauffer D, Kułakowski K. Phase transitions in Nowak-Sznajd opinion dynamics[J]. Physica A: Statistical Mechanics and Its Applications, 2006,378(2): 453-458.
[6]Fortunato S. The Sznajd Consensus model with continuous opinions[ J]. International Journal of Modern Physics C, 2005,16(1): 17 -24.
[7]Stauffer D, Sousa A O, De oliveira S M. Generalization to square lattice of sznajd sociophysics model[ J]. International Journal of Modern Physics C, 2000,11(6): 1239-1245.
[8]Elgazzar A S. Applications of small-world networks to some socio-economic systems[ J]. Physica A: Statistical Mechanics and its Applications, 2003,324(1): 402-407.
[9]Bernardes A T, Stauffer D, Kertészl J. Election results and the sznajd model on barabasi network[J]. The European Physical Journal B, 2002,25(1): 123-127.
[10] 熊莲花, 李玲菲, 王莉. 基于“优先占有”理论的舆论演化模型[J]. 合肥工业大学学报(自然科学版), 2018,41(4): 557-563.
Xiong Lianhua, Li Lingfei, Wang Li. Evolution model of public opinion based on “First Possession” theory [J]. Journal of Hefei University of Technology (Natural Science Edition), 2018, 41(4): 557-563.
[11] 何建佳, 刘举胜. 基于扩展Hegselmann-Krause模型的舆论演化模式研究[J]. 情报科学, 2018,36(1): 158-163.
He Jianjia, Liu Jusheng. Research on public opinion evolution model based on extended Hegselmann-Krause model [J]. Information Science, 2018,36(1): 158-163.
[12] 胡祖平, 何建佳. 基于元胞自动机的网络舆论演化建模及仿真[J]. 情报理论与实践, 2018,41(5): 155-160.
Hu Zuping, He Jianjia. Evolution modeling and simulation of network public opinion based on cellular automata [J]. Information Theory and Practice, 2018,41(5): 155-160.
[13] 刘泉, 荣莉莉, 于凯. 考虑多层邻居节点影响的微博网络舆论演化模型[J]. 系统工程学报, 2017,32(6): 721-731.
Liu Quan, Rong Lili, Yu Kai. Evolution model of microblog network public opinion considering the influence of multilayer neighbor nodes [J]. Journal of Systems Engineering, 2017,32(6): 721-731.
[14] Proskurnikov A V, Tempo R, Cao M, et al. Opinion evolution in time-varying social influence networks with prejudiced agents[J]. IFAC Papers OnLine, 2017,50(1): 11896-11901.
[15] Fan K Q, Pedrycz W. Evolution of public opinions in closed societies influenced by broadcast media[J]. Physica A: Statistical Mechanics and Its Applications, 2017,472: 53-66.
[16] 杨柳, 朱恒民, 马静. 考虑次近邻影响的微博舆论观点演化模型[J]. 现代图书情报技术, 2014(12): 78-84.
Yang Liu, Zhu Hengmin, Ma Jing. Evolution model of microblog public opinion considering the influence of second neighbors [J]. Modern Books and Information Technology, 2014(12): 78-84.
[17] Luo G X, Liu Y, Zeng Q A, et al. A dynamic evolution model of human opinion as affected by advertising[J]. Physica A: Statistical Mechanics and Its Applications, 2014,414: 254-262.
[18] 陈国华, 施茂楠, 袁勒俭, 等. 考虑群体思维的网络舆论演化研究[J]. 情报理论与实践, 2019,42(7): 86-92.
Chen Guohua, Shi Maonan, Yuan Lejian, et al. Research on the evolution of network public opinion considering group thinking [J]. Information Theory and Practice, 2019,42(7): 86-92.
[19] 阮冰, 朱建冲, 姜礼平, 等. 复杂网络上的舆论形成演化建模与仿真研究[J]. 军事运筹与系统工程, 2010,24(1): 53-58.
Ruan Bing, Zhu Jianchong, Jiang Liping, et al. Modeling and simulation of public opinion formation on complex networks [J]. Military Operations and Systems Engineering, 2010,24(1): 53-58.
[20] 任立肖, 张亮, 杜子平, 等. 复杂网络上的网络舆情演化模型研究述评[J]. 情报科学, 2014,32(8): 148-156.
Ren Lixiao, Zhang Liang, Du Ziping, et al. Research on evolution model of network public opinion on complex networks [J]. Information Science, 2014,32(8): 148-156.
[21] 王舰, 王志宏, 张乐君. 复杂网络演化的舆论动力学模型及仿真分析[J]. 计算机应用, 2018,38(4): 1201-1206.
Wang Jian, Wang Zhihong, Zhang Lejun. Public opinion dynamics model and simulation analysis of complex network evolution [J]. Computer Applications, 2018,38(4): 1201-1206.
[22] Wang J W, Rong L L, Deng Qiu Hong,et al. Evolving hypernetwork model[J]. The European Physical Journal B, 2010,77(4): 493-498.
[23] 李倩倩, 刘怡君. 基于超网络的社会舆论演化及应用研究[J]. 中国科学院院刊, 2012,27(5): 569-577.
Li Qianqian, Liu Yijun. Evolution and application of social public opinion based on hypernetwork [J]. Journal of Chinese Academy of Sciences, 2012,27(5): 569-577.
[24] 浦娇华, 朱恒民, 刘凯. 基于动态网络的微博舆论观点演化模型研究[J]. 情报杂志, 2014, 33(8): 168-172.
Pu Jiaohua, Zhu Hengmin, Liu Kai. Evolution model of microblog public opinion based on dynamic network [J]. Journal of Information, 2014,33(8): 168-172.
[25] Chang H, Su B B, Zhou Y P, et al. Assortativity and act degree distribution of some collaboration networks[J]. Physica A: Statistical Mechanics and Its Applications, 2007,383(2): 687-702.
[26] 马涛,郭进利, 王福红, 等. M-G-P型复杂网络中有寿命节点的进入退出机制[J]. 数学的实践与认识, 2017,47(15): 285-292.
Ma Tao, Guo Jinli, Wang Fuhong, et al. Entry and exit mechanism with life nodes in M-G-P complex networks[J]. Mathematics Practice and Understanding, 2017,47(15): 285-292.
[27] 张峰, 吴斌, 王柏, 等. 基于决策偏移的舆论演化动力学模型[J]. 系统工程理论与实践, 2014,34(S1): 172-178.
Zhang Feng, Wu Bin, Wang Bo, et al. Evolution dynamics model of public opinion based on decision migration [J]. Theory and Practice of Systems Engineering, 2014,34(S1): 172-178.
[28] Li T Y, Zhu H M. Effect of the media on the opinion dynamics in online social networks[J]. Physica A: Statistical Mechanics and Its Applications, 2020,551: 124117.
[29] Wang Y, Yao J, Chen G R. An evolving super-network model with inter-vehicle communications[J]. Journal of the Franklin Institute, 2019,356(15): 8665-8689.
[30] Guo J L, Suo Q. Brand effect versus competitiveness in hypernetworks[J]. Chaos, 2015,25(2): 023102.
[31] Wang Z P, Yin H F, Jiang Xin. Exploring the dynamic growth mechanism of social networks using evolutionary hypergraph[J]. Physica A: Statistical Mechanics and Its Applications, 2020,544: 122545.
[32] Berge C. Graphs and Hypergraphs[M]. Amesterdam: North Holland, 1973.
[33] Berge C. Hypergraphs: Combinatorics of Finite Sets[M]. Amesterdam: North Holland, 1989.
[34] Estrada E, Rodríguez-Velázquez J A. Subgraph centrality and clustering in complex hypernetworks[J]. Physica A: Statistical Mechanics and Its Applications, 2005,364: 581-594.
[35] Dorogovtsev S N, Mendes J F F. Evolution of networks with aging of sites[J]. Physical Review E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 2000,62(2):1842-1845.
[36] 郭进利. 复杂网络和人类行为动力学演化模型[M]. 北京: 科学出版社, 2013.
[37] Suo Q, Guo J L, Sun S W, et al. Exploring the evolutionary mechanism of complex supply chain systems using evolving hypergraphs[J]. Physica A: Statistical Mechanics and Its Applications, 2018,489: 141-148.

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