网络舆情演化中群体极化的形成机理研究  被引量:29

Research on the Mechanism for Group Polarization in Online Public Opinion Dynamics

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作  者:王世雄[1] 祝锡永[1] 潘旭伟[1] 姜毅[1] 

机构地区:[1]浙江理工大学管理科学与工程系

出  处:《情报学报》2014年第6期614-622,共9页Journal of the China Society for Scientific and Technical Information

基  金:教育部人文社科基金项目(13YJCZH183);浙江省自然科学基金项目(Y6110332);浙江理工大学科研创新团队专项(13090056-Y)

摘  要:网络舆情演化过程中容易出现意见分化、对立或聚集,产生网络对峙、网络声讨等群体极化现象。为揭示网络舆情演化系统中群体极化现象的特性与形成规律,在分析网络舆情演化中群体极化的内涵、特征和形式的基础上,从网络群体成员的行为规则、交互过程、群体涌现等出发构建网络舆情群体极化的Multi—Agent系统,建立网络舆情演化中的群体极化模型,给出算法实现,并且利用计算实验方法验证群体规模、意见领袖数量、意见领袖观点等对网络舆情演化中群体极化的影响,进而对网络舆情演化中群体极化的形成机理进行系统的研究和诠释。研究有助于把握网络舆情演化规律以及监测网络群体成员的群集行为,有利于对网络舆情的引导和监管。Online social networks provide globally available and prompt services for people to publish, discuss and exchange opinions freely. When a group in these networks exchanges information to format public opinions and is asked to attain a consensus, the obtained consensus is generally more extreme than the average of the initial individual opinions, and lead to group polarization which is a famous phenomenon reported in the social psychology. To obtain an understanding of the mechanism of group polarization in online public opinions dynamic, we analyze interactions between different types of agents including regular agents, leaders and stubborn agents in online social network, and study what kinds of interactions and initial opinion profiles will lead to group opinions shift to polarization. Our work is to extend the classical bounded confidence model and propose an agent-based one which considers interactions between agents and its influence to the emerging of group polarization. The extended model discusses some characteristics such as activeness, influence, uncertainty and reputation for different types of agents. Computational experiments to verify the validity of the model are carried out. The experiments discuss how these characteristics for different types of agents have some influences on the group polarization during online public opinion formation and dynamic. Therefore, we find that group size, the number of leaders and the initial opinions of leaders produce an important effect on group polarization. As a result, group opinion shift to polarization more easily if leaders have extreme opinions. When leaders have similar and extreme opinions initially, group opinion may shift to single extreme convergence called network denunciation. When leaders have antagonistic andextreme opinions, group opinion may shift to double extreme convergence called network confrontation.

关 键 词:网络舆情 舆情演化 群体极化 计算实验 

分 类 号:G206[文化科学—传播学]

 

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