论文标题
模拟个人的分区
Modeling partitions of individuals
论文作者
论文摘要
尽管自我组装群体在动物和人类社会中的核心作用，但解释其组成的统计工具还是有限的。我们介绍了一个统计框架，以对具有独家成员资格的群体进行横断面观察，以阐明使人们聚集在一起的社会和组织机制。拟议的框架从网络和分区的随机模型中汲取灵感，引入了分区分布的指数分布家族。我们得出了其主要的数学特性，并提出了指定和估计此类模型的策略。关于黑客马拉松事件的案例研究将开发的框架应用于研究自组装项目团队形成的机制。
Despite the central role of self-assembled groups in animal and human societies, statistical tools to explain their composition are limited. We introduce a statistical framework for cross-sectional observations of groups with exclusive membership to illuminate the social and organizational mechanisms that bring people together. Drawing from stochastic models for networks and partitions, the proposed framework introduces an exponential family of distributions for partitions. We derive its main mathematical properties and suggest strategies to specify and estimate such models. A case study on hackathon events applies the developed framework to the study of mechanisms underlying the formation of self-assembled project teams.
