基于行为意愿与反转信息可靠性的舆论反转演变研究
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摘要
[目的/意义]舆论反转是舆论衍变的特殊过程。通过分析舆论发生反转的演变条件,有助于提高舆论治理效果。[方法/过程]借鉴Weisbuch-Deffuant模型,引入群体极化的网民行为意愿因素和反转信息可靠程度两个变量,构建Weisbuch-Deffuant-Reversal舆论反转模型。对实验模型中的关键变量对舆论反转的演变过程影响进行分析。[结果/结论]研究发现,在WD-R模型中,μ=0.5时,网民反转观点演化速度更快,系统趋于稳定的速度也更快。网民行为意愿会对网络舆论反转观点聚合产生影响。随着意愿值的逐渐增大,反转舆论形成统一观点所用时间逐渐减小。行为意愿服从均值为0.5的正态分布要比服从随机均匀分布的反转观点演化速度更迅速。反转信息的可靠程度有助于反转观点的收敛。当反转信息的可靠程度越大时,网民产生的反转舆论观点越趋向于客观观点。
[Purpose/Significance]The reversal of public opinion is a special process in the evolution of public opinion. It is helpful for improving the effect of public opinion governance to analyze the evolution conditions of public opinion reversal.[Method/Process]Based on the Weisbuch-Deffuant model, the Weisbuch-Deffuant-Reversal(WD-R)model is constructed by introducing two variables: the netizens' behavioral intention factor of group polarization and the reliability of reverse information. The effects of key variables in the experimental model on the evolution of the reversal of public opinion are analyzed.[Result/Conclusion]The study showed that in the WD-R model, when taking μ=0.5, netizens will change their views more quickly and the system tends to stabilize faster. The behavioral intention will have an impact on the convergence of the reversal of public opinion. With the increase of behavior intention, the time taken for reverse public opinion to form a unified opinion is gradually reduced. The behavioral intention adopting a normal distribution with an average value of 0.5 will make reversed opinions evolve more rapidly than obeying a random uniform distribution. The reliability of the reverse information might help the convergence of the reverse views. When the reliability of the reverse information is greater, the reverse opinions generated by netizens tend to be more objective.
[Purpose/Significance]The reversal of public opinion is a special process in the evolution of public opinion. It is helpful for improving the effect of public opinion governance to analyze the evolution conditions of public opinion reversal.[Method/Process]Based on the Weisbuch-Deffuant model, the Weisbuch-Deffuant-Reversal(WD-R)model is constructed by introducing two variables: the netizens' behavioral intention factor of group polarization and the reliability of reverse information. The effects of key variables in the experimental model on the evolution of the reversal of public opinion are analyzed.[Result/Conclusion]The study showed that in the WD-R model, when taking μ=0.5, netizens will change their views more quickly and the system tends to stabilize faster. The behavioral intention will have an impact on the convergence of the reversal of public opinion. With the increase of behavior intention, the time taken for reverse public opinion to form a unified opinion is gradually reduced. The behavioral intention adopting a normal distribution with an average value of 0.5 will make reversed opinions evolve more rapidly than obeying a random uniform distribution. The reliability of the reverse information might help the convergence of the reverse views. When the reliability of the reverse information is greater, the reverse opinions generated by netizens tend to be more objective.
引文
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[16] 汪明艳,余丽彬,朱译冰.舆论反转中群体极化效应的影响因素研究[J].情报杂志,2018,37(9):106-112,119.
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[21] Trilling D,Klingeren M V,Tsfati Y. Selective exposure,political polarization,and possible mediators: Evidence from the netherlands[J]. International Journal of Public Opinion Research,2017,29(2):189-213.
[22] Suhay E. Explaining group influence: The role of identity and emotion in political conformity and polarization[J].Political Behavior,2015,37(1):221-251.
[23] Smith E R,Seger C R,Mackie D M. Can emotions be truly group level? Evidence regarding four conceptual criteria[J]. Journal of Personality & Social Psychology,2007,93(3):431-446.
[24] Cowan S K,Baldassarri D."It could turn ugly": Selective disclosure of attitudes in political discussion networks[J].Social Networks,2018,52:1-17.
[25] 吴越,杜亚军,陈晓亮,等.基于新曝光冲突性消息的网络舆论逆转研究[J].物理学报,2016,65(3):46-55.
[2] 王玉龙.舆情反转:突发事件过程中网络群体极化的角色研究——基于“天价鱼事件”的分析[J].电子政务,2016(5):16-24.
[3] Gérard Weisbuch,Deffuant G ,Frédéric Amblard. Persuasion dynamics[J]. Physica a statistical Mechanics & Its Applications,2004,353(1):555-575.
[4] Bhattacharyya A,Braverman M,Chazelle B,et al. On the Convergence of the hegselmann-krause system[J]. Physics,2013:61-66.
[5] Kayal S . Unsupervised image segmentation using the Deffuant-weisbuch model from social dynamics[J]. Signal Image & Video Processing,2017,11(8):1405-1410.
[6] Del Vicario M,Scala A,Caldarelli G,et al. Modeling confirmation bias and polarization[J]. Scientific Reports,2017(7):1-12.
[7] Chen G,Cheng H,Huang C,et al.Deffuant model on a ring with repelling mechanism and circular opinions[J]. Physical Review E,2017,95(4):042118.
[8] Meng X F,VanGorder R A,Porter M A. Opinion formation and distribution in a bounded-confidence model on various networks[J]. Physical Review E,2018,97(2):1-24.
[9] 黄炜,余辉,李岳峰,等.网络舆情事件演化的仿真实践研究[J].现代情报,2017,37(8):65-73.
[10] 赵剑华,万克文.基于信息传播模型-SIR传染病模型的社交网络舆情传播动力学模型研究[J].情报科学,2017,35(12):34-38.
[11] 胡珑瑛,董靖巍.网络舆情演进过程参与主体策略行为仿真和政府引导[J].中国软科学,2016(10):50-61.
[12] 陈培友,侯甜甜,李明.移动社交网络舆情多主体应对的系统动力学仿真研究[J].情报科学,2018,36(6):25-29,34.
[13] 陈福集,翁丽娟.基于系统动力学的移动环境下高校网络舆情应对策略研究[J].现代情报,2018,38(4):118-123,176.
[14] 朱侯,胡斌.信息与情绪驱动的舆论演化的QSIM-ABS模拟[J].情报学报,2016,35(3):310-316.
[15] 张丽,朱侯,万芳彬,叶碧云,赵琴琴.考虑信息与组织氛围影响的网络舆论反转模拟[J].情报科学,2018,36(5):57-63.
[16] 汪明艳,余丽彬,朱译冰.舆论反转中群体极化效应的影响因素研究[J].情报杂志,2018,37(9):106-112,119.
[17] Lee S Y. How do people compare themselves with others on social network sites? :The case of facebook[J].Computers in Human Behavior,2014,32(C):253-260.
[18] Butzer B,Kuiper N.A. Relationships between the frequency of social comparisons and self-concept clarity,intolerance of uncertainty,anxiety,and depression[J]. Personality and Individual Differences,2006,41(1):167-176.
[19] Emily M Cramer,Hayeon Song,Adam M Drent. Social comparison on facebook: Motivation,affective consequences,self-esteem,and Facebook fatigue[J]. Computers in Human Behavior,2016,64:739-746.
[20] Levendusky M,Malhotra N. Does media coverage of partisan polarization affect political Attitudes?[J]. Political Communication,2016,33(2):283-301.
[21] Trilling D,Klingeren M V,Tsfati Y. Selective exposure,political polarization,and possible mediators: Evidence from the netherlands[J]. International Journal of Public Opinion Research,2017,29(2):189-213.
[22] Suhay E. Explaining group influence: The role of identity and emotion in political conformity and polarization[J].Political Behavior,2015,37(1):221-251.
[23] Smith E R,Seger C R,Mackie D M. Can emotions be truly group level? Evidence regarding four conceptual criteria[J]. Journal of Personality & Social Psychology,2007,93(3):431-446.
[24] Cowan S K,Baldassarri D."It could turn ugly": Selective disclosure of attitudes in political discussion networks[J].Social Networks,2018,52:1-17.
[25] 吴越,杜亚军,陈晓亮,等.基于新曝光冲突性消息的网络舆论逆转研究[J].物理学报,2016,65(3):46-55.