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Choosing Your Neighbors: Networks of Diffusion in International Relations


  • Authors’ note: Previous versions of this paper were presented at the 2010 International Studies Association Annual Meeting in New Orleans, LA, and the 2010 American Political Science Association Annual Meeting in Washington, DC. We wish to acknowledge useful comments and insights from Abraham Flaxman, Gary King, Patrick Lam, Miya Woolfalk, Paul Hensel, Andrew Thomas, Dale Thomas, and seminar participants at the Institute for Quantitative Social Science. We are particularly grateful to Gary King for inspiring the Conflicting Neighbor Problem. Remaining errors are our own. We also want to thank Kristian Skrede Gleditsch and Michael D. Ward for making complete replication data and code easily available for use. Brandon Stewart gratefully acknowledges support from a National Science Foundation Graduate Research Fellowship. Replication materials and maps are currently available upon request and will be posted to the authors’ Dataverse upon publication.


Zhukov, Yuri M. and Brandon M. Stewart. (2012) Choosing Your Neighbors: Networks of Diffusion in International Relations. International Studies Quarterly, doi: 10.1111/isqu.12008
© 2012 International Studies Association

In examining the diffusion of social and political phenomena like regime transition, conflict, and policy change, scholars routinely make choices about how proximity is defined and which neighbors should be considered more important than others. Since each specification offers an alternative view of the networks through which diffusion can take place, one’s decision can exert a significant influence on the magnitude and scope of estimated diffusion effects. This problem is widely recognized, but is rarely the subject of direct analysis. In international relations research, connectivity choices are usually ad hoc, driven more by data availability than by theoretically informed decision criteria. We take a closer look at the assumptions behind these choices, and propose a more systematic method to asses the structural similarity of two or more alternative networks, and select one that most plausibly relates theory to empirics. We apply this method to the spread of democratic regime change and offer an illustrative example of how neighbor choices might impact predictions and inferences in the case of the 2011 Arab Spring.