网络背书动态中的层次结构
Emergence of Hierarchy in Networked Endorsement Dynamics
摘要：
许多社会和生物系统的特点是持久的等级制度，包括那些围绕学术界的声望，动物群体的统治地位和网上约会的可取性而组织的等级制度。尽管它们无处不在，但解释这种等级制度的产生和持久性的一般机制还没有得到很好的理解。我们引入了一个生成模型的动态层次结构，使用时变网络中，新的链接是根据当前网络中的节点的偏好形成的，旧的链接随着时间的推移被遗忘。该模型产生了一系列的层次结构，从平等主义到非平等的层次结构，我们得到的临界点，这些制度的限制，长期的系统记忆。重要的是，我们的模型支持统计推断，允许使用数据对生成机制进行原则性比较。我们应用该模型来研究数学家之间的招聘模式，长尾小鹦鹉之间的优势关系，以及兄弟会成员之间的友谊的经验数据中的层次结构，观察几个持久的模式，以及每个人所青睐的生成机制的可解释的差异。我们的工作有助于不断增长的文献统计接地模型的时变网络。
英文摘要：
Many social and biological systems are characterized by enduring hierarchies, including those organized around prestige in academia, dominance in animal groups, and desirability in online dating. Despite their ubiquity, the general mechanisms that explain the creation and endurance of such hierarchies are not well understood. We introduce a generative model for the dynamics of hierarchies using time-varying networks in which new links are formed based on the preferences of nodes in the current network and old links are forgotten over time. The model produces a range of hierarchical structures, ranging from egalitarianism to bistable hierarchies, and we derive critical points that separate these regimes in the limit of long system memory. Importantly, our model supports statistical inference, allowing for a principled comparison of generative mechanisms using data. We apply the model to study hierarchical structures in empirical data on hiring patterns among mathematicians, dominance relations among parakeets, and friendships among members of a fraternity, observing several persistent patterns as well as interpretable differences in the generative mechanisms favored by each. Our work contributes to the growing literature on statistically grounded models of time-varying networks.
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