
Contents
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Network Beginnings Network Beginnings
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Three Barriers Facing Sociological Network Analysis Three Barriers Facing Sociological Network Analysis
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Data Dependency as a Solution, not a Problem Data Dependency as a Solution, not a Problem
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Networks in Political Science and the So-Called Dyad Networks in Political Science and the So-Called Dyad
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Spatial Analysis and Social Networks Spatial Analysis and Social Networks
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Bipartite Latent Space Networks Bipartite Latent Space Networks
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Dynamic Latent Space Networks Dynamic Latent Space Networks
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Criticisms of Latent Space Networks Criticisms of Latent Space Networks
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Conclusion Conclusion
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Notes Notes
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References References
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10 Latent Networks and Spatial Networks in Politics
Get accessCassy Dorff holds a Ph.D. in Political Science from Duke University (2015) and is Assistant Professor of Political Science at the University of New Mexico. Her research on conflict studies, international relations, social movements, network analysis, and forecasting has been published in the American Journal of Political Science, International Studies Review, Political Science Research and Methods, International Interactions, and elsewhere.
Shahryar Minhas holds a Ph.D. in Political Science from Duke University and will be an Assistant Professor in the Department of Political Science and Social Science Data Analytics Program at Michigan State University in 2017. His research on quantitative methods, political economy, and international relations has been published in International Interactions, Journal of Conflict Resolution, Journal of Peace Research, and Research and Politics.
Michael D. Ward holds a Ph.D. in Political Science from Northwestern University (1977) and is professor of Political Science at Duke University. He is coauthor of Spatial Regression Models with Kristian S. Gleditsch (Sage Publications 2008) and his research on international relations, political economy, and security has been published in the American Journal of Political Science, International Organization, Journal of Conflict Resolution, and elsewhere.
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Published:10 May 2017
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Abstract
Network analysis is a growing field in political science, with topics ranging from the study of individual actors in congressional networks to international war between countries. This chapter briefly summarizes the history of network analysis, the barriers facing previous approaches, and current innovations, with an emphasis on latent variable approaches. These approaches provide an organic link to the consideration of spatial networks, also discussed in detail. These innovations expand researchers’ ability to capture the many different facets of network-motivated questions, including how networks evolve or how spatial proximity determines network ties. The chapter concludes with a brief comparison of two major types of latent variable models and their relation to other network approaches commonly used in political science.
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