| 摘要: |
| 目的 探究空间因素对群体观点演化的影响,进一步认识空间因素在社会观点演化过程中所起到的关键作
用。 方法 有界影响 Hegselmann-Krause(HK)模型中的信任矩阵区分为局域信任矩阵和非局域信任矩阵两种,把个
体观点放置到具有物理空间属性的正方格子上,从而构建出具有空间因素的有界影响 HK 模型。 在数值模拟过程
中,通过选取随机排序或顺序排序不同的初始观点,以及不同影响权重下的信任矩阵,发现具有空间因素的有界影
响 HK 模型可以模拟信息闭塞的社会和网络信息社会中群体观点的演化过程。 结果 数值模拟显示:在只有局域信
任矩阵作用下且初始观点为顺序排序时,个体观点首先在局域形成了局域共识后再达成全局性的共识,模拟了在
信息闭塞环境下群体观点演化情况;当初始观点为随机排序时,个体观点在局域未形成局域共识而是直接演化为
了全局共识,模拟了信息社会中群体观点的演化过程。 结论 研究表明:在局域信任矩阵和非局域信任矩阵共同作
用下,在影响权重相同的情况下,信任矩阵的取值越大群体观点最大族数减少的越快;影响权重大小表示信息传播
范围的大小,影响权重的大小可以加快或延缓群体观点演化的形成,也可以控制观点族数的数值大小。 |
| 关键词: 观点动力学 HK 模型 有界影响 观点演化 |
| DOI： |
| 分类号: |
| 基金项目: |
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| Study on Local and Non-local Spatial Social Group Opinion Evolution Based on an Improved and Extended HKModel |
|
ZHANG Jiangyan
1
ZHAO Jianhui
2
|
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1. Center for Economic Research on the Upper Reaches of the Yangtze River Chongqing Technology and Business
University Chongqing 400067 China
2. Chongqing Municipal Public Security Bureau Chongqing 401147 China
|
| Abstract: |
| Objective This study examines the evolution of social group opinions in physical space to understand the
critical role of spatial factors in opinion dynamics. Methods By placing individual opinions on a square grid and
distinguishing the bounded confidence Hegselmann -Krause HK model?? s trust matrix into local and non -local trust
matrices a spatially bounded confidence HK model is constructed. By selecting different initial opinions and trust
matrices with varying influence weights the evolution of group opinions in both information - isolated societies and
networked information societies can be simulated. Results Numerical simulations reveal that when only the local trust
matrix is active and initial opinions are sequentially arranged individual opinions first form local consensus before
achieving global consensus. This simulates the evolution of group opinions in an information - isolated environment.Conversely when initial opinions are randomly arranged individual opinions do not form local consensus but instead
evolve directly into global consensus. This simulates the evolution of group opinions in an information society. Conclusion
The study demonstrates that under the combined influence of local and non-local trust matrices with the same influence
weight a larger trust matrix value accelerates the reduction of the maximum number of opinion clusters. The influence
weight reflects the scope of information dissemination its magnitude can either expedite or delay the formation of group
opinion evolution as well as control the number of opinion clusters. |
| Key words: opinion dynamics HK model bounded influence opinion evolution |
