论文标题
社交网络中的统计推断：如何取样偏见和不确定性形状决策
Statistical inference in social networks: how sampling bias and uncertainty shape decisions
论文作者
论文摘要
我们根据对社会关系的观察，使用统计推论来研究个人如何使用统计推断形成对人口行为的期望。对他人的联系和行为的误解是由于友谊悖论和小样本的不确定性引起的采样偏见引起的。在动作是战略补充的游戏中，我们表征了平衡并分析平衡行为。我们允许代理复杂化解决采样偏差，并证明复杂性如何影响平衡。我们展示了种群行为如何取决于误解的来源，并说明了与采样偏见相比，抽样不确定性何时起着至关重要的作用。
We investigate how individuals form expectations about population behavior using statistical inference based on observations of their social relations. Misperceptions about others' connectedness and behavior arise from sampling bias stemming from the friendship paradox and uncertainty from small samples. In a game where actions are strategic complements, we characterize the equilibrium and analyze equilibrium behavior. We allow for agent sophistication to account for the sampling bias and demonstrate how sophistication affects the equilibrium. We show how population behavior depends on both sources of misperceptions and illustrate when sampling uncertainty plays a critical role compared to sampling bias.
