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复杂系统与复杂性科学  2024, Vol. 21 Issue (3): 30-37    DOI: 10.13306/j.1672-3813.2024.03.005
  复杂网络 本期目录 | 过刊浏览 | 高级检索 |
网络舆情中基于心理暗示的温和舆论引导策略研究
刘与同, 陈曦
华中科技大学人工智能与自动化学院,武汉 430074
Moderate Online Opinion Guidance Strategy Based on Psychological Suggestion
LIU Yutong, CHEN Xi
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
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摘要 为应对网络舆论环境中信息茧房效应的消极影响,考虑在舆论引导过程中将个体对引导观点的接受程度,提出基于心理暗示的温和观点引导策略,并构建了基于心理暗示的温和引导策略模型。通过实验分析了引导强度与引导比例的影响,研究了引导策略对舆论演化过程的影响,并在多个网络下验证了引导策略的稳定性,最后与传统度引导策略进行了对比。结果表明温和引导在引导效果具有优越性,尤其是能在中长期对群体舆论进行持续影响。
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刘与同
陈曦
关键词 观点演化线上舆情温和舆论引导心理暗示    
Abstract:To cope with the negative impact of the information cocoon effect in the network public opinion environment, we take the individual′s acceptance of guiding opinion into consideration, propose a moderate opinion guidance strategy based on psychological suggestion, and propose a moderate opinion dynamic model. We analyze the influence of guidance strength and guidance ratio through simulation experiments, and the influence of moderate guidance strategy on the evolution process of public opinion is studied. Then, we verify the stability of the bootstrapping strategy under multiple networks and compares it with traditional degree booting. The results show the superiority of moderate guidance in guiding effect, especially in the long term.
Key wordsopinion dynamics    online opinion    moderateopinion guidance    phycological suggestion
收稿日期: 2022-12-21      出版日期: 2024-11-07
ZTFLH:  TB391.9  
  C94  
基金资助:国家自然科学基金(71974063)
通讯作者: 陈曦(1974-),男,湖北武汉人,博士,教授,主要研究方向为复杂系统、决策支持理论与方法。   
作者简介: 刘与同(1998-),男,湖南长沙人,硕士研究生,主要研究方向为复杂系统建模与仿真。
引用本文:   
刘与同, 陈曦. 网络舆情中基于心理暗示的温和舆论引导策略研究[J]. 复杂系统与复杂性科学, 2024, 21(3): 30-37.
LIU Yutong, CHEN Xi. Moderate Online Opinion Guidance Strategy Based on Psychological Suggestion[J]. Complex Systems and Complexity Science, 2024, 21(3): 30-37.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2024.03.005      或      https://fzkx.qdu.edu.cn/CN/Y2024/V21/I3/30
[1] SUNSTEIN C R. Republic. com[M]. Princeton: Princeton University Press, 2001.
[2] JAMIESON K H, CAPPELLA J N. Echo chamber: rush Limbaugh and the conservative media establishment[M]. Oxford: Oxford University Press, 2008.
[3] IYENGAR S, HAHN K S. Red media, blue media: evidence of ideological selectivity in media use[J]. Journal of Communication, 2009, 59(1): 19-39.
[4] LAWRENCE E, SIDES J, FARRELL H. Self-segregation or deliberation? blog readership, participation, and polarization in American politics[J]. Perspectives on Politics, 2010, 8(1): 141-157.
[5] FLAXMAN S, GOEL S, RAO J M. Filter bubbles, echo chambers, and online news consumption[J]. Public Opinion Quarterly, 2016, 80(Special Issue1): 298-320.
[6] 何建佳,胡祖平. 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.
HE J, HU Z. Modeling and simulation of network public opinion evolution based on cellular automata[J]. Information Studies: Theory & Application, 2018,41(5):155-160.
[7] 计永超, 刘莲莲. 新闻舆论引导力:理论渊源、现实依据与提升路径[J]. 新闻与传播研究, 2016,23(9):15-26,126.
JI Y, LIU L. Guidance of news: theoretical origin, practical basis and improvement path[J]. Journalism & Communication, 2016,23(9):15-26,126.
[8] FLYNN L R, GOLDSMITH R E, EASTMAN J K. Opinion leaders and opinion seekers: two new measurement scales[J]. Journal of the Academy of Marketing Science, 1996, 24(2): 137-147.
[9] DAVIS R L. Accelerating the diffusion of innovations using opinion leaders[J]. Annals, 1999,556(1): 55-67.
[10] PASTOR-SATORRAS R, VESPIGNANI A. Immunization of complex networks[J]. Physical Review E-Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 2002, 65(3): 1-8.
[11] COHEN R, HAVLIN S, BEN-AVRAHAM D. Efficient immunization strategies for computer networks and populations[J]. Physical Review Letters, 2003, 91(24): 2-5.
[12] GARGIULO F, GANDICA Y. The role of homophily in the emergence of opinion controversies[J]. Journal of Artificial Societies and Social Simulation, 2017, 20(3):8.
[13] LARSEN K S. Conformity in the asch experiment[J]. Journal of Social Psychology, 1974, 94(2): 303-304.
[14] CASTELLANO C, FORTUNATO S, LORETO V. Statistical physics of social dynamics[J]. Reviews of Modern Physics, 2009, 81(2): 591-646.
[15] FLACHE A, MACY M W. Small worlds and cultural polarization[J]. Journal of Mathematical Sociology, 2011, 35(1-3): 146-176.
[16] DEFFUANT G, NEAU D, AMBLARD F, et al. Mixing beliefs among interacting agents[J]. Advances in Complex Systems, 2000, 3(4): 87-98.
[17] HEGSELMANN R, KRAUSE U. Opinion dynamics and bounded confidence models, analysis and simulation[J]. Journal of Artificial Societies and Social Simulation, 2002, 5(3):2.
[18] CAMPBELL A, GURIN G, MILLER W E. The Voter Decides[M].Oxford, England: Row, Peterson, and Co, 1954.
[19] SOOD V, REDNER S. Voter model on heterogeneous graphs[J]. Physical Review Letters, 2005, 94(17): 6-9.
[20] SZNAJD-WERON K. Sznajd model and its applications[J]. Acta Physica Polonica B, 2005, 36(8): 2537-2547.
[21] YANG D, LIAO X, SHEN H, et al. Dynamic node immunization for restraint of harmful information diffusion in social networks[J]. Physica A: Statistical Mechanics and Its Applications, 2018, 503: 640-649.
[22] IOANNIDIS E, VARSAKELIS N, ANTONIOU I. Change agents and internal communications in organizational networks[J]. Physica A: Statistical Mechanics and Its Applications, 2019, 528: 121385.
[23] SABIDUSSI G. The centrality index of a graph[J]. Psychometrika, 1966, 31(4): 581-603.
[24] FREEMAN L C. A set of measures of centrality based on betweenness[J]. American Sociological Association, 1977, 40(1): 35-41.
[25] VALENTE T W, PUMPUANG P. Identifying opinion leaders to promote behavior change[J]. Health Education and Behavior, 2007, 34(6): 881-896.
[26] CHEN D, LÜ L, SHANG M S, et al. Identifying influential nodes in complex networks[J]. Physica A: Statistical Mechanics and Its Applications, 2012, 391(4): 1777-1787.
[27] Qian C, Cao J, Lu J, et al. Adaptive bridge control strategy for opinion evolution on social networks[J]. Chaos: an Interdisciplinary Journal of Nonlinear Science, 2011, 21(2): 025116.
[28] Chen X, Xiong X, Zhang M, et al. Public authority control strategy for opinion evolution in social networks[J]. Chaos: an Interdisciplinary Journal of Nonlinear Science, 2016, 26(8): 083105.
[29] AFSHAR M, ASADPOUR M. Opinion formation by informed agents[J]. Journal of Artificial Societies and Social Simulation, 2010, 13(4):5
[30] ZHAO Y, KOU G, PENG Y, et al. Understanding influence power of opinion leaders in e-commerce networks: an opinion dynamics theory perspective[J]. Information Sciences, 2018, 426: 131-147.
[31] 张轩宇,陈曦,肖人彬.后真相时代基于敌意媒体效应的观点演化建模与仿真[DB/OL].[2022-06-24]. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C45S0n9fL2suRadTyEVl2pW9UrhTDCdPD65FzzQr8IgOxMTUujzlt9MGZG3cQV-UiqPngqocS_bONte_6UebBG4-&uniplatform=NZKPT.
XUANYU Z, XI C, RENBIN X.Modeling and simulation of opinion evolution based on hostile media effect in the post-truth era[DB/OL].[2022-06-24]. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C45S0n9fL2suRadTyEVl2pW9UrhTDCdPD65FzzQr8IgOxMTUujzlt9MGZG3cQV-UiqPngqocS_bONte_6UebBG4-&uniplatform=NZKPT.
[32] 肖人彬,刘琪. 观点动力学视角下基于意见领袖的网络舆情反转研究[J]. 复杂系统与复杂性科学, 2019,16(1):1-13.
XIAO R, LIU Q. Anopinion dynamics approach to public opinion reversion with the guidance of opinion leaders[J]. Complex Systems and Complexity Science, 2019,16(1):1-13.
[33] 张镕,张云中,王依婷. 基于情感分析的媒体型智库舆论引导力测度研究[J]. 情报理论与实践, 2021, 44(4), 130-137.
ZHANG R, ZHANG Y, WANG Y.Research on public opinion guidance measurement of media-based think tanks based on sentiment analysis[J]. Information Studies: Theory & Application, 2021, 44(4), 130-137.
[34] 张镕,张云中. 基于扎根理论的媒体型智库舆论引导力构成与作用机制研究[J]. 情报理论与实践, 2021,44(11),80-88.
ZHANG R, ZHANG Y. Research oncomposition and mechanism of media-based think tanks’ public opinion guidance based on grounded theory[J]. Information Studies: Theory & Application, 2021,44(11),80-88.
[35] WEBSTER D M, KRUGLANSKI A W. Individual differences in need for cognitive closure[J]. Journal of Personality and Social Psychology, 1994, 67(6): 1049.
[36] MILLER MCPHERSON, LYNN SMITH-LOVIN, JAMES M. COOK. Birds of a feather: homophily in social networks[J]. Annual Review of Sociology, 2001, 27: 415-444.
[37] 谢耘耕, 荣婷. 微博舆论生成演变机制和舆论引导策略[J]. 现代传播:中国传媒大学学报, 2011, 178(5): 70-74.
XIE Y, RONG T.Weibo opinion dynamics and guidance strategy[J]. Modern Communication(Journal of Communication University of China), 2011, 178(5): 70-74.
[38] LEE L, FREDERICK S, ARIELY D. Try it, you’ ll like it[J]. Psychological Science, 2006, 17(12): 1054-1059.
[39] MCCLUNG M, COLLINS D. “Because I know it will!”: placebo effects of an ergogenic aid on athletic performance[J]. Journal of Sport & Exercise Psychology, 2007, 29(3): 382-394.
[40] MICHAEL R B, GARRY M, KIRSCH I. Suggestion, cognition, and behavior[J]. Current Directions in Psychological Science, 2012, 21(3): 151-156.
[41] PARKER S, GARRY M, EINSTEIN G O, et al. A sham drug improves a demanding prospective memory task[J]. Memory, 2011, 19(6): 606-612.
[42] YIN X, WANG H, YIN P, et al. Agent-based opinion formation modeling in social network: a perspective of social psychology[J]. Physica A: Statistical Mechanics and Its Applications, 2019, 532:121786
[43] CHAZELLE B, WANG C. Inertial hegselmann-krause systems[J]. IEEE Transactions on Automatic Control, 2017, 62(8): 3905-3913.
[44] CHEN X, ZHAO S, LI W. Opinion dynamics model based on cognitive styles: field-dependence and field-independence[J]. Complexity, 2019, 2019(1):2864124.
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