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A Local Structure Graph Model: Modeling Formation of Network Edges as a Function of Other Edges

  • Olga V. Chyzh (a1) and Mark S. Kaiser (a2)


Localized network processes are central to the study of political science, whether in the formation of political coalitions and voting blocs, balancing and bandwagoning, policy learning, imitation, diffusion, tipping-point dynamics, or cascade effects. These types of processes are not easily modeled using traditional network approaches, which focus on global rather than local structures within networks. We show that localized network processes, in which network edges form in response to the formation of other edges, are best modeled by shifting from the traditional theoretical framework of nodes-as-actors to what we term a nodes-as-actions framework, which allows for zeroing in on relationships among network connections. We show that the proposed theoretical framework is statistically compatible with a local structure graph model (LSGM). We demonstrate the properties of LSGMs using a Monte Carlo experiment and explore action–reaction processes in two empirical applications: formation of alliances among countries and legislative cosponsorships in the US Senate.


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Authors’ note: Replication materials are available from the Political Analysis Dataverse (Chyzh and Kaiser 2018). Previous versions of this paper have been presented at Polmeth 2016 at Rice University, at Peace Science 2016 at the University of Notre Dame, at PolNet 2016 at Washington University in St. Louis, at PolNet 2017 at The Ohio State University, at the “Studying Politics in Time and Space” 2017 workshop at Texas  A&M University, and at the 2017 online International Methods Colloquium. We thank all the discussants and participants of these conferences for their feedback. We especially thank Vera Troeger, Scott Cook, Guy Whitten, Bruce Desmarais, Justin Esarey, Chris Zorn, Mark Nieman and Robert Urbatsch.

Contributing Editor: Jeff Gill



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Political Analysis
  • ISSN: 1047-1987
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