[论文解读] Social Influences in the Voter Model: the Role of Conformity.

Marco Alberto Javarone|arXiv (Cornell University)|Jan 4, 2014

Opinion Dynamics and Social Influence被引用 1

一句话总结

本文提出了一种在联网结构上运行的投票者模型，其中包含从众与非从众行为的个体，个体根据邻近个体的选择更新观点——从众者遵循多数意见，非从众者遵循少数意见。关键发现表明，非从众者密度在系统动态中起决定性作用：从众者在完全连通网络中起到稳定作用，但在复杂网络中则会引发不稳定，且仅当非从众者行为极端时，网络拓扑结构才具有决定性影响。

ABSTRACT

We study the effects of social influences in opinion dynamics. In particular, we define a simple model, based on the majority rule voting, in order to consider the role of conformity. Conformity is a central issue in social psychology as it represents one of people's behaviors that emerges as a result of their interactions. The proposed model represents agents, arranged in a network and provided with an individual behavior, that change opinion in function of those of their neighbors. In particular, agents can behave as conformists or as nonconformists. In the former case, agents change opinion in accordance with the majority of their social circle (i.e., their neighbors); in the latter case, they do the opposite, i.e., they take the minority opinion. Moreover, we investigate the nonconformity both on a global and on a local perspective, i.e., in relation to the whole population and to the social circle of each nonconformist agent, respectively. We perform a computational study of the proposed model, with the aim to observe if and how the conformity affects the related outcomes. Moreover, we want to investigate whether it is possible to achieve some kind of equilibrium, or of order, during the evolution of the system. Results highlight that the amount of nonconformist agents in the population plays a central role in these dynamics. In particular, conformist agents play the role of stabilizers in fully-connected networks, whereas the opposite happens in complex networks. Furthermore, by analyzing complex topologies of the agent network, we found that in the presence of radical nonconformist agents the topology of the system has a prominent role; otherwise it does not matter since we observed that a conformist behavior is almost always more convenient. Finally, we analyze the results of the model by considering that agents can change also their behavior over time.

研究动机与目标

• 研究社会从众与非从众行为如何影响结构化群体中的意见动态。
• 建模个体行为（从众者与非从众者）与网络拓扑结构之间的相互作用，以揭示系统层面的结果。
• 确定在从众者与非从众者比例变化时，系统是否会出现稳定均衡。
• 分析随时间演变的行为适应如何影响系统的长期行为。

提出的方法

• 个体被嵌入网络中，并根据邻近个体的选择使用多数规则（从众者）或少数规则（非从众者）来更新观点。
• 该模型区分了全局非从众与局部非从众：非从众者将其观点与整体人群或其直接社交圈进行比较。
• 在完全连通网络与复杂网络上进行计算模拟，以比较不同拓扑结构下的系统行为。
• 通过追踪意见分布与稳定性随时间的变化，评估系统是否收敛至均衡或持续波动。
• 允许个体在从众与非从众行为之间动态切换，以模拟行为适应过程。

实验结果

研究问题

• RQ1 非从众者比例如何影响系统整体秩序或均衡的出现？
• RQ2 当存在非从众者时，网络拓扑在塑造意见形成动态中起到何种作用？
• RQ3 从众行为是否在所有网络结构中都起到稳定作用，还是其效果取决于拓扑结构？
• RQ4 在何种条件下，非从众者会引发持续波动而非收敛？
• RQ5 个体能够随时间在从众与非从众行为之间切换时，如何影响系统的长期稳定性？

主要发现

• 在完全连通网络中，从众者起到稳定作用，促进共识的形成。
• 在复杂网络中，从众者可能使系统变得不稳定，尤其是在存在非从众者的情况下。
• 仅当非从众者行为极端时，网络拓扑才变得重要，否则无论结构如何，从众行为都会占主导地位。
• 具有局部非从众性（其邻近群体中的少数）的非从众者，其不稳定性影响强于具有全局非从众性的个体。
• 当个体能够随时间切换行为时，系统往往趋向于一种动态均衡，意见分布持续波动，尤其是在存在非从众者的情况下。
• 该模型表明，在复杂拓扑结构中，从众与非从众行为之间的平衡是维持系统长期秩序的必要条件。