复杂网络中无信任边界限制的连续观点演化研究  

Research of Evolution of Continuous Opinions without Bounded Confidence in Complex Network

作　　者：苟智坚[1,2] 范明钰[1] 王光卫[1] 

机构地区：[1]电子科技大学计算机科学与工程学院成都610054 [2]成都信息工程学院信息安全工程学院成都610025

出　　处：《电子科技大学学报》2015年第5期749-756,共8页Journal of University of Electronic Science and Technology of China

基　　金：国家863计划(2009AA01Z435)

摘　　要：多数的连续观点演化模型中,缺少考虑舆论环境对信任关系的影响,同时信任边界条件使得观点演化聚合之后,各观点集合中的个体无法进行后续观点交互。该文分析个体观点差异以及邻居舆论环境对交互过程中信任关系的影响,消除信任边界对观点交互更新的限制,建立无观点信任边界限制的连续观点演化模型,并研究该模型观点演化统一的影响机制。理论分析与仿真实验表明:该模型不单可以反映观点演化的聚合过程,而且能反映舆论演化聚合之后各观点集合之间的竞争交互过程,模型可描述观点集合形成后的观点有序集合的变化;同时,模型反映了在较高聚类系数的无标度网络中,观点演化统一更加困难,而在平均连接度高的网络中,演化统一更加容易,这与已有相关研究结论是基本相符的。Most models about continuous opinion dynamics lack the considerations of the effects of public opinion environment on trust relationships, and when opinions have been clustered into some collections, the bounded confidence will impede the subsequent opinion interactions between individuals that come from different opinion collections. In this paper, the change mechanism of trust relationships which affected by difference of opinion and neighboring opinion environment is analyzed, the restrictions of bounded confidence on individual interactions is eliminated, and a general model for the evolution of continuous opinions without bounded confidence is proposed. The results of simulation and of analysis show that our model not only reflect the opinions polymerization process, but also reflect the subsequent opinion interactions between individuals in different opinion collections after opinions have been aggregated. In addition, our model can do better at reflecting and explaining the process of opinion evolution, and it is consistent with existing search conclusions that the opinions consensus probability will be reduce if the clustering coefficient of complex network has been increased and will be increased with the addition of average degree.

关 键 词：信任边界 复杂网络 连续观点 观点演化 

分 类 号：TP393.02[自动化与计算机技术—计算机应用技术]