Machine learningDynamic network inference
Stochastic Actor-Oriented Model
The stochastic actor-oriented model (SAOM), implemented in the SIENA software, is a framework for analyzing the dynamics of social networks observed at two or more time points. It treats observed network panels as snapshots of an unobserved continuous-time process in which actors, at stochastically timed moments, evaluate their local network and decide whether to create, maintain, or drop a tie so as to improve their position according to an objective function.
在 MethodMind 中打开即将推出应用、比较、获取指导
工具与资源
学习与探索
视频即将推出
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
方法图谱
相关方法的邻域——选择一个节点以展开探索。
来源
- Snijders, T. A. B. (2001). The statistical evaluation of social network dynamics. Sociological Methodology, 31(1), 361–395. DOI: 10.1111/0081-1750.00099 ↗
- Snijders, T. A. B., van de Bunt, G. G., & Steglich, C. E. G. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32(1), 44–60. DOI: 10.1016/j.socnet.2009.02.004 ↗
如何引用本页
ScholarGate. (2026, June 22). Stochastic Actor-Oriented Model (SAOM / SIENA). ScholarGate. https://scholargate.app/zh/sociology/stochastic-actor-oriented-model
选用哪种方法?
将本方法与其最相近的同类并置,并排研读——本馆将书籍铺陈于案上,取舍则由您定夺。
- Homophily AnalysisSociology↔ 比较
- Latent Space Network ModelSociology↔ 比较
- Relational Event ModelSociology↔ 比较
- 社会网络分析网络分析↔ 比较