标题： 具有异质偏见的集体决策：网络拓扑结构和易感性的作用 显示英文标题

标题： Collective decision-making with heterogeneous biases: Role of network topology and susceptibility

摘要： 群体做出准确集体决策的能力取决于各种因素的复杂相互作用，例如先验信息、偏见、社会影响以及交互网络的结构。 在这里，我们研究了一个自旋模型，该模型考虑了异质性偏好，并能够控制社会互动的非线性。 在之前对完全图和规则二维晶格的研究基础上，我们研究了将网络拓扑修改为（稀疏）随机图如何影响集体决策。 我们使用两种不同的敏感度测量方法来评估系统对内部和外部扰动的响应能力。 特别是，我们研究了敏感度的最大值如何依赖于网络连通性。 基于我们的发现，我们讨论了集体系统如何通过调整其网络结构或社会互动的性质，以适应环境波动的变化，从而保持在最大敏感度区域。 显示英文摘要

摘要： The ability of groups to make accurate collective decisions depends on a complex interplay of various factors, such as prior information, biases, social influence, and the structure of the interaction network. Here, we investigate a spin model that accounts for heterogeneous preferences and enables control over the non-linearity of social interactions. Building on previous results for complete graphs and regular 2D lattices, we investigate how the modification of network topology towards (sparse) random graphs can affect collective decision-making. We use two different measures of susceptibility to assess the responsiveness of the system to internal and external perturbations. In particular, we investigate how the maximum of susceptibility depends on network connectivity. Based on our findings, we discuss how collective systems might adapt to changes in environmental fluctuations by adjusting their network structure or the nature of their social interactions in order to remain in the region of maximal susceptibility.