摘要
[目的/意义]从定量化角度研究舆情群体极化现象,建立网络舆情群体极化度的量化计算和极化趋势预测方法。[方法/过程]从物理学中场的思想出发,引入观点势场描述舆情场内各网民节点间观点的相互作用,构建个体观点势和舆情场观点势场强度的计算模型和观点演化模型;该模型考虑了实际网络舆情传播的天然社区特性、节点观点影响力特性、观点的惯性特性和网民节点虚实的时变特性,认为个体网民观点的演化主要受所处舆情场的观点势强度、自身观点惯性的影响;通过仿真实验,重点分析模型中舆情子场是否封闭、节点虚实转换触发阀值、观点势影响因子等影响因素对网络舆情群体极化的影响。[结果/结论]仿真结果表明该模型与实际网络舆情观点传播与舆情极化形成过程较为相符。所提出的模型中网民观点间的相互作用通过舆情场这个中介完成,相较于基于网民个体之间观点直接相互作用的舆情演化模型,其复杂性和实现难度大大降低,利于基于模型构建实际网络舆情极化预测与监控系统。
[ Purpose/significance The Public opinion group polarization phenomenon is studied from the perspective of quantitative, to establish the quantitative calculation and polarization trend prediction method. [ Method/process ] In- spired from the idea of Physical fields, the interaction between the users nodes in the public opinion field is described by introducing the view potential field, and an opinion potential field intensity calculation model and opinion evolvement mod- el of the individual power and public opinion is proposed. The natural community feature of actual network public opinion transmission, influence feature of node opinion, inertial feature of opinion and time-varying feature of virtual or true node is taken into account in the model. This model maintains that the netizen opinion evolvement is controlled by Internet pub- lic opinion field intensity and opinion inertial feature. Based on the simulation experiment, the model analyses the influ- ence of the public opinion field connectivity, the node type conversion trigger threshold and the opinion potential influence coefficient on public opinion group polarization. [ Result/conclusion] Simulation results show that the model agrees with the actual public opinion polarization evolution process, in which the public opinion field is used as the intermediary to present the interplay of netizen opinions. Compared with the model based on direct interaction, its complexity and implementation difficulty are greatly reduced, which is conducive to building a practical Public Opinion Monitoring System.
出处
《图书情报工作》
CSSCI
北大核心
2015年第19期108-112,121,共6页
Library and Information Service
基金
教育部人文社会科学研究项目"基于观点势场演化的舆情极化预测模型研究"(项目编号:13YJCZH197)研究成果之一
关键词
互联网舆情场
观点演化
舆情极化
仿真
Internet public opinion field opinion evolvement public opinion polarization simulation