DYNAMIC-MODEL FOR SOCIAL NETWORKS
DYNAMIC-MODEL FOR SOCIAL NETWORKS
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DOI：
10.1080/0022250x.1977.9989862
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发表时间：
1977-01-01
影响因子：
1
通讯作者：
LEINHARDT, S
中科院分区：
文献类型：
--
作者：
HOLLAND, PW;LEINHARDT, S
一个连续时间的二进制矩阵值马尔可夫链被用来模拟社会结构影响个人行为的过程。该模型是在人际影响的社会计量网络的背景下开发的。通过将网络看作一个时间依赖的随机过程，我们可以构建跃迁强度方程，来描述群成员之间的选择发生变化的概率。这些方程可以包含结构效应的参数。参数的经验估计值可以解释为结构趋势的度量。描述了一些基本过程，并根据过程的稳态解解释了模型在横截面数据中的应用。
A continuous‐time binary‐matrix‐valued Markov chain is used to model the process by which social structure effects individual behavior. The model is developed in the context of sociometric networks of interpersonal affect. By viewing the network as a time‐dependent stochastic process it is possible to construct transition intensity equations for the probability that choices between group members will change. These equations can contain parameters for structural effects. Empirical estimates of the parameters can be interpreted as measures of structural tendencies. Some elementary processes are described and the application of the model to cross‐sectional data is explained in terms of the steady state solution to the process.