Publication

Stochastic Actor-Oriented Models for Network Dynamics

Snijders, T. & Pickup, M., Sep-2017, The Oxford Handbook of Political Networks. Victor, J. N., Montgomery, A. H. & Lubell, M. (eds.). Oxford: Oxford University Press, 29 p.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

  • Thomas Snijders
  • Mark Pickup
Stochastic Actor Oriented Models for Network Dynamics are used for the statistical analysis of longitudinal network data collected as a panel. The probability model defines an unobserved stochastic process of tie changes, where social actors add new ties or drop existing ties in response to the current network structure; the panel observations are snapshots of the resulting changing network. The statistical analysis is based on computer simulations of this process, which provides a great deal of flexibility in representing data constraints and dependence structures. In this Chapter we begin by defining the basic model. We then explicate a new model for nondirected ties, including several options for the specification of how pairs of actors coordinate tie changes. Next, we describe coevolution models. These can be used to model the dynamics of several interdependent sets of variables, such as the analysis of panel data on a network and the behavior of the actors in the network, or panel data on two or more networks. We finish by discussing the differences between Stochastic Actor Oriented Models and some other longitudinal network models. A major distinguishing feature is the treatment of time, which allows straightforward application of the model to panel data with different time lags between waves. We provide a variety of applications in political science throughout.
Original languageEnglish
Title of host publicationThe Oxford Handbook of Political Networks
EditorsJennifer Nicoll Victor, Alexander H. Montgomery, Mark Lubell
Place of PublicationOxford
PublisherOxford University Press
Number of pages29
ISBN (Print)9780190228217
Publication statusPublished - Sep-2017

    Keywords

  • Siena, longitudinal network models, panel data, directed networks, nondirected networks, two-sided choices, coordination, coevolution, model specification, inferential network analysis

ID: 54519745