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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.

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Sources

  1. Snijders, T. A. B. (2001). The statistical evaluation of social network dynamics. Sociological Methodology, 31(1), 361–395. DOI: 10.1111/0081-1750.00099
  2. 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

How to cite this page

ScholarGate. (2026, June 22). Stochastic Actor-Oriented Model (SAOM / SIENA). ScholarGate. https://scholargate.app/en/sociology/stochastic-actor-oriented-model

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ScholarGateStochastic Actor-Oriented Model (Stochastic Actor-Oriented Model (SAOM / SIENA)). Retrieved 2026-06-24 from https://scholargate.app/en/sociology/stochastic-actor-oriented-model · Dataset: https://doi.org/10.5281/zenodo.20539026