论文标题
一种用于检测网络社区的结构模型
A Structural Model for Detecting Communities in Networks
论文作者
论文摘要
本文的目的是在互动和学习的背景下识别和分析一组嵌入子网络中的玩家的响应动作。我们将战略网络形成描述为一种静态的交互游戏，其中玩家根据他们建立的连接和多种相互依存的动作来最大程度地发挥其效用，这些动作允许玩家的特定于小组特定参数。将这种类型的模型应用于现实生活中的情况是有挑战性的，原因有两个：贝叶斯纳什平衡的计算高度要求很高，社会影响力的识别需要使用排除的变量，而这些变量通常不可用。基于理论建议，我们提出了一组模拟方程，并讨论了采用多模式网络自回归的社会互动效应的识别。
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.
