Analyzing Social Networks as Stochastic Processes
Analyzing Social Networks as Stochastic Processes
复制标题
将社交网络分析为随机过程
DOI：
--
复制
发表时间：
1980
期刊：
影响因子：
--
通讯作者：
S. Wasserman
中科院分区：
文献类型：
--
作者：
S. Wasserman
摘要本文提出了一种新的方法来研究人际关系的社会网络，基于随机建模的变化，随着时间的推移发生在网络上。具体来说，我们假设这些变化可以建模为一个连续时间马尔可夫链。链的转移率取决于一小组参数，这些参数衡量社会结构各个方面对变化概率的重要性。我们讨论了框架的假设，并描述了两个简单的模型，它的应用程序。然后，我们提出，分析和解释几个例子，我们概述了参数估计的方法。这些模型被证明是非常有效的，使我们能够更好地理解网络的演变。
Abstract This article presents a new methodology for studying a social network of interpersonal relationships, based on stochastic modeling of the changes that occur in the network over time. Specifically, we postulate that these changes can be modeled as a continuous-time Markov chain. The transition rates for the chain are dependent on a small set of parameters that measure the importance of various aspects of social structure on the probability of change. We discuss the assumptions of the framework and describe two simple models that are applications of it. We then present, analyze, and interpret several examples, and we outline methods of parameter estimation. The models prove to be quite effective and allow us to better understand the evolution of a network.