Stochastic Actor-Oriented Models for the Co-Evolution of Networks and Behavior: An Introduction and Tutorial

Yuval Kalish*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Stochastic actor-oriented (SAO) models are a family of models for network dynamics that enable researchers to test multiple, often competing explanations for network change and estimate the extent and relative power of various influences on network evolution. SAO models for the co-evolution of network ties and actor behavior, the most comprehensive category of SAO models, examine how networks and actor attributes—their behavior, performance, or attitudes—influence each other over time. While these models have been widely used in the social sciences, and particularly in educational settings, their use in organizational scholarship has been extremely limited. This paper provides a layperson introduction to SAO models for the co-evolution of networks and behavior and the types of research questions they can address. The models and their underpinnings are explained in nonmathematical terms, and theoretical explanations are supported by a concrete, detailed example that includes step-by-step model building and hypothesis testing, alongside an R script.

Original languageEnglish
Pages (from-to)511-534
Number of pages24
JournalOrganizational Research Methods
Volume23
Issue number3
DOIs
StatePublished - 1 Jul 2020

Keywords

  • RSiena
  • longitudinal models
  • social network analysis
  • stochastic actor-oriented models

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