标题： 一种用于检测网络中社区的结构模型 显示英文标题

标题： A Structural Model for Detecting Communities in Networks

摘要： 本文的目的是在互动和学习的背景下，识别和分析嵌入子网络中的一组玩家的响应行为。 我们将战略网络形成描述为一种静态互动博弈，其中玩家根据他们建立的连接以及允许玩家组特定参数的多个相互依赖的行为来最大化其效用。 由于两个原因，将这种模型应用于现实场景具有挑战性：贝叶斯纳什均衡的计算需求很高，而社会影响的识别需要使用通常不可用的排除变量。 基于理论建议，我们提出了一组模拟方程，并讨论了利用多模态网络自回归模型的社会互动效应的识别。 显示英文摘要

摘要： The objective of this paper is to identify and analyze the response actions of a set of players embedded in sub-networks in the context of interaction and learning. We characterize strategic network formation as a static game of interactions where players maximize their utility depending on the connections they establish and multiple interdependent actions that permit group-specific parameters of players. It is challenging to apply this type of model to real-life scenarios for two reasons: The computation of the Bayesian Nash Equilibrium is highly demanding and the identification of social influence requires the use of excluded variables that are oftentimes unavailable. Based on the theoretical proposal, we propose a set of simulant equations and discuss the identification of the social interaction effect employing multi-modal network autoregressive.