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现代图书情报技术  2015, Vol. 31 Issue (11): 60-67     https://doi.org/10.11925/infotech.1003-3513.2015.11.09
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
媒体干预下带有讨论机制的网络舆情传播模型研究
张立凡, 赵凯
南京邮电大学管理学院 南京 210023
Study on the Internet Public Opinion Dissemination Model with Discussion Under the Effect of Media
Zhang Lifan, Zhao Kai
College of Management, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
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摘要 

[目的]通过构建带有讨论机制的舆情传播模型, 研究媒体作用下网络舆情演变的内在规律。[方法]把媒体对舆情传播的干预作用抽象为强化度及分歧度, 构建新的SIaIbR模型。根据舆情传播动力学方程, 求解系统传播阈值, 证明传播平衡点的稳定性。[结果]仿真结果显示, 分歧度对于传播的影响要远大于强化度, 当分歧度低于0.5时候, 政府介入有助于网络舆情更快平息。[局限]仿真所用均为模拟数据, 未能结合真实传播事例进行分析。[结论]研究成果为政府利用媒体干预舆情传播提供支持, 也为进一步研究媒体干预下舆情传播问题提供参考。

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Abstract

[Objective] By building a dissemination model with a discussion of Internet public opinion, the paper studies the inner rule of the public opinion evolution. [Methods] Present a new dissemination model with a discussion of the mechanism named SIaIbR, and express the impact of media on public opinion with the concept of Enhanced Degree and Divergence. According to dynamics equations, the equilibrium point and stability of the model are proved.[Results] The result of simulation shows that relative to the Enhanced Degree, the Divergence has an even greater impact on the dissemination of Internet public opinion. When Divergence is lower than 0.5, the government has a great impact on putting down the public opinion.[Limitations] Without combining reality disseminate examples.[Conclusions] The results can help the government take measures when facing the problem of Internet public opinion propagation, and also provide some references for the further research on Internet public opinion.

收稿日期: 2015-05-04      出版日期: 2016-04-06
:  C931  
  G53  
基金资助:

本文系国家自然科学基金项目“互联网舆情演化中群体行为协同演进模型研究”(项目编号:71271120)的研究成果之一。

通讯作者: 赵凯, ORCID: 0000-0002-8706-4968, E-mail: 1102533026@qq.com。     E-mail: 1102533026@qq.com
作者简介: 作者贡献声明:张立凡: 提出研究思路, 设计研究方案; 赵凯: 实施研究方案, 论文起草及最终版本修订。
引用本文:   
张立凡, 赵凯. 媒体干预下带有讨论机制的网络舆情传播模型研究[J]. 现代图书情报技术, 2015, 31(11): 60-67.
Zhang Lifan, Zhao Kai. Study on the Internet Public Opinion Dissemination Model with Discussion Under the Effect of Media. New Technology of Library and Information Service, 2015, 31(11): 60-67.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2015.11.09      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2015/V31/I11/60

[1] Zhou J, Liu Z, Li B. Influence of Network Structure on Rumor Propagation [J]. Physics Letters A, 2007, 368(6): 458-463.
[2] Han S, Zhuang F, He Q, et al. Energy Model for Rumor Propagation on Social Networks [J]. Physica A: Statistical Mechanics & Its Applications, 2014, 394: 99-109.
[3] Zanette D. Dynamics of Rumor Propagation on Small-world Networks [J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2002, 65(4): 110-126.
[4] Moreno Y, Nekovee M, Pacheco A F. Dynamics of Rumor Spreading in Complex Networks [J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2004, 69(6): 279-307.
[5] 陈波, 于泠, 刘君亭, 等. 泛在媒体环境下的网络舆情传播控制模型[J]. 系统工程理论与实践, 2011, 31(11): 2140-2150. (Chen Bo, Yu Ling, Liu Junting, et al. Dissemination and Control Model of Internet Public Opinion in the Ubiquitous Media Environments [J]. Systems Engineering ——Theory & Practice, 2011, 31(11): 2140-2150.)
[6] Crokidakis N. Effects of Mass Media on Opinion Spreading in the Sznajd Sociophysics Model [J]. Physica A: Statistical Mechanics & Its Applications, 2012, 391: 1729-1734.
[7] 朱恒民, 刘凯, 卢子芳. 媒体作用下互联网舆情话题传播模型研究[J]. 现代图书情报技术, 2013(3): 45-50. (Zhu Hengmin, Liu Kai, Lu Zifang. Study on Topic Propagation Model of Internet Public Opinion Under the Influence of the Media [J]. New Technology of Library and Information Service, 2013(3): 45-50.)
[8] Zhao L, Cui H, Qiu X, et al. SIR Rumor Spreading Model in the New Media Age [J]. Physica A: Statistical Mechanics & Its Applications, 2013, 392:995-1003.
[9] Qian Z, Tang S, Zhang X, et al. The Independent Spreaders Involved SIR Rumor Model in Complex Networks [J]. Physica A: Statistical Mechanics and Its Applications, 2015, 429: 95-102.
[10] Kermack W O, McKendrick A G. Contributions to the Mathematical Theory of Epidemics [J]. Bulletin of Mathematical Biology, 1991, 53(1-2): 33-55.
[11] Gonalez-Parra G, Arenas A J, Chen-Charpentier B M. Combination of Nonstandard Schemes and Richardson's Extrapolation to Improve the Numerical Solution of Population Models [J]. Mathematical and Computer Modeling, 2010, 52(7-8): 1030-1036.
[12] 廖晓昕. 动力系统的稳定性理论和应用[M]. 北京: 国防工业出版社, 2000. (Liao Xiaoxin.Theory and Application of Stability for Dynamical Systems[M].Beijing: National Defense Industry Press, 2000.)
[13] Van den Driessche P, Watmough J. Reproduction Numbers and Sub-threshold Endemic Equilibria for Compartmental Models of Disease Transmission [J]. Mathematical Biosciences, 2002, 180(1-2): 29-48.
[14] Stuart A M, Humphries A R. Dynamic System and Numerical Analysis [M]. New York: Cambridge University Press, 1996: 22-24.

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