Political opinion formation: Initial opinion distribution and individual heterogeneity of tolerance
Political opinion formation: Initial opinion distribution and individual heterogeneity of tolerance
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政治观点的形成：初始观点分布和个体宽容度的异质性
DOI：
10.1016/j.physa.2016.10.025
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发表时间：
2017-02
影响因子：
3.3
通讯作者：
Jin Xiaogang
中科院分区：
文献类型：
--
作者：
Jin Cheng;Li Yifu;Jin Xiaogang
网络上的意见动态因其在社会行为和自组织系统中的深远前景而受到严重关注。然而，政治舆论形成作为一个典型而重要的案例，却一直缺乏讨论。以前的基于代理的模拟提出了各种模型，是基于不同的机制，如网络拓扑结构和状态转换之间的协同进化。然而，即使在相同的网络拓扑结构下，使用相同的简单机制，形成意见仍然是不确定的。在这项工作中，我们提出了两个特点，意见的初始分布和个人的异质性容忍的意见变化，在政治意见的形成。这两个特征嵌入在经典模型的网络构建阶段。本文通过对单一多党制的比较，沿着对两党制的详细分析，发现在持续稳定阶段和持续稳定过程中，都存在着分裂、两极分化和共识化的关键现象。我们进一步引入最近邻的平均比率来表征意见形成的阶段。结果表明，在相似的随机网络上，意见的初始分布会导致不同的演化结果。此外，顽固节点的存在也起到了特殊的作用：只有极端顽固的节点才能引起最终意见分布的变化，而在其他情况下，它们只会延迟达到稳定的时间。如果顽固节点的数量很少，它们的影响被限制在一个小范围内。本文的理论工作是对现有模型的进一步深化，是对政党竞争定性和定量模拟的初步探索。
Opinion dynamics on networks have received serious attention for its profound prospects in social behaviours and self-organized systems. However, political opinion formation, as one typical and significant case, remains lacking in discussion. Previous agent-based simulations propose various models that are based on different mechanisms like the coevolution between network topology and status transition. Nonetheless, even under the same network topology and with the same simple mechanism, forming opinions can still be uncertain. In this work, we propose two features, the initial distribution of opinions and the individual heterogeneity of tolerances on opinion changing, in political opinion formation. These two features are imbedded in the network construction phase of a classical model..By comparing multi simple-party systems, along with a detailed analysis on the two-party system, we capture the critical phenomenon of fragmentation, polarization and consensus both in the persistent stable stage and in-process. We further introduce the average ratio of nearest neighbours to characterize the stage of opinion formation. The results show that the initial distribution of opinions leads to different evolution results on similar random networks. In addition, the existence of stubborn nodes plays a special role: only nodes that are extremely stubborn can cause the change of final opinion distribution while in other.cases they only delay the time to reach stability. If stubborn nodes are small in number, their effects are confined within a small range. This theoretical work goes deeper on an existing model, it is an early exploration on qualitative and quantitative simulation of party competition.
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