Introduction to stochastic actor-based models for network dynamics
Introduction to stochastic actor-based models for network dynamics
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DOI：
10.1016/j.socnet.2009.02.004
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发表时间：
2010-01-01
期刊：
影响因子：
3.1
通讯作者：
Steglich, Christian E. G.
中科院分区：
文献类型：
--
作者：
Snijders, Tom A. B.;van de Bunt, Gerhard G.;Steglich, Christian E. G.
基于随机参与者的模型是一种网络动力学模型，它可以表示对网络变化的各种影响，并允许估计表达这些影响的参数，并检验相应的假设。网络中的节点代表社会行为者，关系的集合代表社会关系。这些假设假设网络的演化是一个“由参与者驱动”的随机过程，也就是说，该模型特别适合于代表关于参与者如何改变其离任关系的理论。平局变化的概率部分是内生的，即作为当前网络结构本身的函数，并且部分是外生的，作为节点的特征(参与者协变量)和节点对的特征(并元协变量)的函数。在扩展形式中，基于参与者的随机模型可以用于分析社会网络上的纵向数据以及参与者不断变化的属性：网络的动力学和行为。重点是理解模型的基本原理，理解结果，以及模型选择的合理规则。皇冠版权所有(C)2009由爱思唯尔出版。保留所有权利。
Stochastic actor-based models are models for network dynamics that can represent a wide variety of influences on network change, and allow to estimate parameters expressing such influences, and test corresponding hypotheses. The nodes in the network represent social actors, and the collection of ties represents a social relation. The assumptions posit that the network evolves as a stochastic process 'driven by the actors', i.e., the model lends itself especially for representing theories about how actors change their outgoing ties. The probabilities of tie changes are in part endogenously determined, i.e., as a function of the current network structure itself, and in part exogenously, as a function of characteristics of the nodes ('actor covariates') and of characteristics of pairs of nodes ('dyadic covariates'). In an extended form, stochastic actor-based models can be used to analyze longitudinal data on social networks jointly with changing attributes of the actors: dynamics of networks and behavior.This paper gives an introduction to stochastic actor-based models for dynamics of directed networks, using only a minimum of mathematics. The focus is on understanding the basic principles of the model, understanding the results, and on sensible rules for Model selection. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.