|
|
A Research About the Best Time Points for the Government to Intervene Network Public Opinion |
Chen Nan, Wang Hengshan |
Department of System Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China |
|
|
Abstract This paper introduces the traditional social-welfare game model into the BA scale-free network to find out the relationship between the model and the evolutionary process of the public opinion. Taking into account of the study and imitative behaviors to the other gamers in the information structure, it carries on the simulation experiment, and gets the conclusion that small-world effects have positive impact on the information communication and gambling result, so it is a useful tool for government, while propagation speed and the opportunity when the government should control the public opinion are cooperated to influence the information dissemination. In a word, it is not that the earlier the government steps in, the better result we can see.
|
Received: 29 January 2012
Published: 19 April 2012
|
|
[1] 中国互联网络信息中心.第28次中国互联网络发展状况统计报告[R/OL].[2011-12-16].http:/ /www.cnnic.cn/sy/201107/t20110719_22133.html.(CNNIC. The 28th Internet Development Statistics Report of China [R/OL].[2011-12-16].http:/ /www.cnnic.cn/sy/201107/t20110719_22133.html.)[2] Hegselmann R,Krause U. Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation[J].Journal of Artificial Societies and Social Simulation, 2002, 5(3):216-219.[3] Weisbuch G. Bounded Confidence and Social Networks[J]. The European Physical Journal B: Condensed Matter and Complex Systems, 2004, 38(2):339-343.[4] Lorenz J. Consensus Strikes Back in the Hengselmann-Krause Model of Continuous Opinion Dynamics Under Bounded Confidence[J]. Journal of Artificial Societies and Social Simulation, 2006, 9(1):8-22.[5] Yan G, Fu Z Q, Ren J, et al. Collective Synchronization Induced by Epidemic Dynamics on Complex Networks with Communities [J]. Physical Review E, 2007,75(1):1-5.[6] Zhao H, Gao Z Y. Modular Effects on Epidemic Dynamics in Small-World Networks [J]. Europhysics Letters, 2007, 79(3):1-3.[7] Sudbury A J. The Proportion of the Population Never Hearing a Rumour[J]. Applied Probability Trust,1985,22(2):443-446.[8] Zhou T, Liu J G,Bai W J, et al. Behaviors of Susceptible-infected Epidemics on Scale-free Networks with Identical Infectivity[J].Physical Review E, 2006, 74(5):1-6.[9] 王根生,勒中坚,陆旭,等.迁移元胞自动机网络舆情演化模型(M2CA)[J]. 情报学报,2011,30(6): 570-576. (Wang Gensheng, Le Zhongjian, Lu Xu,et al. Model of Opinions Public Evolution Based on Cellular Automaton [J]. Journal of the China Society for Scientific and Technical Information, 2011,30(6): 570-576.)[10] 韩少春,刘云,张彦超,等.基于动态演化博弈论的舆论传播羊群效应[J]. 系统工程学报,2011,26(2):275-281. (Han Shaochun,Liu Yun,Zhang Yanchao,et al. Herd Instinct of Opinion Based on Dynamic Evolutionary Game Theory [J]. Journal of Systems Engineering, 2011,26(2):275-281.)[11] Golder S A,Wilkinson D M,Huberman B A. Rhythms of Social Interaction: Messaging Within a Massive Online Network [C]. In: Proceedings of the 3rd Communities and Technologies Conference. 2007:41-66.[12] 刘志明,刘鲁.微博网络舆情中的意见领袖识别及分析[J]. 系统工程,2011,29(6):8-16.(Liu Zhiming, Liu Lu. Recognition and Analysis of Opinion Leaders in Microblog Public Opinions [J]. Systems Engineering, 2011,29(6):8-16.)[13] 张维迎.博弈论与信息经济学[M].上海:上海人民出版社,2004:135-137.(Zhang Weiying. Game Theory and Information Economics [M].Shanghai: Shanghai People’s Publishing House, 2004: 135-137.) |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|