基于有向加权网络的舆情演化仿真研究
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摘要
【目的/意义】研究舆情演化机制,分析影响舆情演化过程中的因素,为控制舆情的发展提供有力的参考。【方法/过程】本文构建有向加权网络拓扑结构,选用经典Deffuant模型的交互思路并进行改进,重点加入了有向边的权重值,考虑意见领袖的出度,建立交互模型,利用Netlogo软件对现实世界网络舆情的演化进行仿真,分析群体中节点度、意见领袖对群体观点演化过程的影响。【结果/结论】群体中节点度的增大,在一定的度值δ内可以迅速增加个体观点聚合速度,使群体中观点分布更加明显,有利于小范围内观点的统一。意见领袖在群体观点演化中起着关键性作用,对于群体观点的聚合速度有着较大的影响,因此对意见领袖观点的把控有利于更好地引导舆情的发展。
【Purpose/significance】To study the evolution mechanism of public opinion, analyze the factors influencing the evolution of public opinion, and provide a powerful reference for controlling the development of public opinion.【Method/process】This paper constructs a directed weighted network topology, selects the interaction idea of the classic Deffuant model and improves it. It focuses on adding the weight value of the directed edge, considering the degree of opinion leader,establishing an interaction model, and using Netlogo software. The evolution of real world network public opinion is simulated, and the influence of node degree and opinion leader on the evolution process of group opinion is analyzed.【Results/conclusion】The increase of node degree in the population can rapidly increase the aggregation speed of individual viewpoints within a certain degree of value δ, which makes the distribution of viewpoints in the group more obvious, which is conducive to the unification of viewpoints in a small scope. Opinion leaders play a key role in the evolution of group views, and have a greater impact on the speed of group views. Therefore, the control of opinion leaders is conducive to better guiding the development of lyrics.
【Purpose/significance】To study the evolution mechanism of public opinion, analyze the factors influencing the evolution of public opinion, and provide a powerful reference for controlling the development of public opinion.【Method/process】This paper constructs a directed weighted network topology, selects the interaction idea of the classic Deffuant model and improves it. It focuses on adding the weight value of the directed edge, considering the degree of opinion leader,establishing an interaction model, and using Netlogo software. The evolution of real world network public opinion is simulated, and the influence of node degree and opinion leader on the evolution process of group opinion is analyzed.【Results/conclusion】The increase of node degree in the population can rapidly increase the aggregation speed of individual viewpoints within a certain degree of value δ, which makes the distribution of viewpoints in the group more obvious, which is conducive to the unification of viewpoints in a small scope. Opinion leaders play a key role in the evolution of group views, and have a greater impact on the speed of group views. Therefore, the control of opinion leaders is conducive to better guiding the development of lyrics.
引文
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2张敏,霍朝光,吴郁松.时间敏感型网络的ICSR传播模型构建与仿真[J].图书馆学研究,2015,(21):40-48.
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5陈静.复杂网络上基于流行病学的舆情传播模型及其规律研究[D].长春:吉林大学,2013.
6 K Sznajd-Weron,J Sznajd.Opinion Evolution in Closed Community[J].International Journal of Modern Physics C,2000,11(6):1157-1165.
7 Deffuant G,Neau D,Amblard F,et al.Mixing Beliefs Among Interacting Agents[J].Advances in Complex Systems,2000,(3):87-98.
8 R Hegselmann,U Krause.Opinion Dynamics and Bounded Confidence Models[J].Journal of Artifical Societies and Social Simulation,2002,5(3):1-32.
9 Grauwin S,Jensen P.Opinion Groups Formation and Dynamics:Structures That Last from Non Lasting Entities[J].Physical Review E,2012,85(6):66.
10吴鹏,杨爽,张晶晶,高庆宁.突发事件网络舆情中网民群体行为演化的Agent建模与仿真研究[J].现代图书情报技术,2015,(7):65-72.
11张亚楠,孙士保,张京山,尹立航,闫晓龙.基于节点亲密度和影响力的社交网络舆论形成模型[J].计算机应用,2017,37(4):1083-1087.
12李根强,罗艳艳,臧学莲.基于有界信任模型的网络社群舆情观点演化研究[J].情报科学,2017,35(6):63-68.
13 M Pineda,R Toral,E Hernandez-Garcia.Noisy Continuous-opinion Dynamics[J].Journal of Statistical Mechanics:Theory and Experiment,2009,(1):54.
14张伟,何明升,白淑英.基于Weisbuch-Deffuant模型的网络舆论演化模式研究[J].情报杂志,2013,32(7):43-48.
15孙凌.社交网络中的信息与影响力传播模式研究[D].北京:北京交通大学,2016.
2张敏,霍朝光,吴郁松.时间敏感型网络的ICSR传播模型构建与仿真[J].图书馆学研究,2015,(21):40-48.
3 Sudbury A.The Proportion of the Population Never Bearing a Rumour[J].Journal of Applied Probability,1985,(22):443-446.
4陈波,于泠,刘君亭.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.
5陈静.复杂网络上基于流行病学的舆情传播模型及其规律研究[D].长春:吉林大学,2013.
6 K Sznajd-Weron,J Sznajd.Opinion Evolution in Closed Community[J].International Journal of Modern Physics C,2000,11(6):1157-1165.
7 Deffuant G,Neau D,Amblard F,et al.Mixing Beliefs Among Interacting Agents[J].Advances in Complex Systems,2000,(3):87-98.
8 R Hegselmann,U Krause.Opinion Dynamics and Bounded Confidence Models[J].Journal of Artifical Societies and Social Simulation,2002,5(3):1-32.
9 Grauwin S,Jensen P.Opinion Groups Formation and Dynamics:Structures That Last from Non Lasting Entities[J].Physical Review E,2012,85(6):66.
10吴鹏,杨爽,张晶晶,高庆宁.突发事件网络舆情中网民群体行为演化的Agent建模与仿真研究[J].现代图书情报技术,2015,(7):65-72.
11张亚楠,孙士保,张京山,尹立航,闫晓龙.基于节点亲密度和影响力的社交网络舆论形成模型[J].计算机应用,2017,37(4):1083-1087.
12李根强,罗艳艳,臧学莲.基于有界信任模型的网络社群舆情观点演化研究[J].情报科学,2017,35(6):63-68.
13 M Pineda,R Toral,E Hernandez-Garcia.Noisy Continuous-opinion Dynamics[J].Journal of Statistical Mechanics:Theory and Experiment,2009,(1):54.
14张伟,何明升,白淑英.基于Weisbuch-Deffuant模型的网络舆论演化模式研究[J].情报杂志,2013,32(7):43-48.
15孙凌.社交网络中的信息与影响力传播模式研究[D].北京:北京交通大学,2016.