Introduction to stochastic actor-based models for network dynamics

By Tom A. B. Snijders, Gerhard G. van de Bunt, Christian E. G. Steglich. Soc. Networks, 2010

2,064 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/da2f07816a28d69a1b879969283a2693c0b88b2a

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In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

Social Network Analysis in the Science of Groups: Cross-Sectional and Longitudinal Applications for Studying Intra- and Intergroup Behavior (2015, background): “However, among cognitively capable network members, longitudinal network researchers can study all kinds of interdependencies including friendship ties (Snijders et al., 2010), cooperative ties (Lomi, Snijders, Steglich, & Torló, 2011), or conflictual ties (Huitsing et al.”
Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey (2020, background): “Stochastic actor oriented models (SAOM) are continuous-time models which consider each node an actor and model actor behaviour.”
Proximity and Innovation: From Statics to Dynamics (2015, background): “Empirically, separating selection and influence mechanisms is difficult and it requires specific statistical models for network dynamics (SNIJDERS et al., 2010; STEGLICH et al., 2010).”
Exponential random graph models for multilevel networks (2013, methodology): “…h E E i E t E w t e a c t a e p T m 2 a a e n m l n w b a t l 1 tudied simultaneously using the stochastic actor oriented models SAOMs) proposed by Snijders et al. (2010) with longitudinal data. ecent methods to analyze cross-sectional network data include xponential random graph models (ERGMs)…”
The Dynamics of Technical and Business Knowledge Networks in Industrial Clusters: Embeddedness, Status, or Proximity? (2016, background): “For a general introduction to SAOMs, see Snijders et al. (2010), for more technical details see Snijders et al. (2010).”
A Separable Model for Dynamic Networks (2010, methodology): “The terms in the model are structurally largely consistent with the terms chosen in Snijders et al. (2010).”
Tools and methods in participatory modeling: Selecting the right tool for the job (2018, methodology): “More complex stochastic models have been designed for handling network independencies, such as Exponential Random Graph Models, or ERGMs (Robins et al., 2007) and Stochastic Actor Oriented Models (SAOMs) (Snijders et al., 2010).”
The dynamics of interfirm networks along the industry life cycle: The case of the global video game industry, 1987–2007 (2013, background): “Another reason is that statistical models to handle such data have been developed only very recently (Snijders et al., 2010).”