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Statistical inference for multilayer networks in political science

Published online by Cambridge University Press:  11 November 2019

Ted Hsuan Yun Chen Open the ORCID record for Ted Hsuan Yun Chen [Opens in a new window]
Ted Hsuan Yun Chen*
Affiliation:
Aalto University and University of Helsinki, Finland
*
*Corresponding author. E-mail: [email protected]
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Abstract

Interactions between units in political systems often occur across multiple relational contexts. These relational systems feature interdependencies that result in inferential shortcomings and poorly-fitting models when ignored. General advancements in inferential network analysis have improved our ability to understand relational systems featuring interdependence, but developments specific to working with interdependence that cross relational contexts remain sparse. In this paper, I introduce a multilayer network approach to modeling systems comprising multiple relations using the exponential random graph model. In two substantive applications, the first a policy communication network and the second a global conflict network, I demonstrate that the multilayer approach affords inferential leverage and produces models that better fit observed data.

Keywords

Civil/domestic conflictenvironmental politics and policyinternational conflictquantitative methods
Type
Original Article
Information
Political Science Research and Methods , Volume 9 , Issue 2 , April 2021 , pp. 380 - 397
Copyright
Copyright © The European Political Science Association 2019

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References

Allansson, M, Melander, E and Themnér, L (2017) Organized violence, 1989–2015. Journal of Peace Research 54, 727–742.Google Scholar
Alter, KJ and Meunier, S (2009) The politics of international regime complexity. Perspectives on Politics 7, 13–24.CrossRefGoogle Scholar
Boccaletti, S, Bianconi, G, Criado, R, Del Genio, CI, Gómez-Gardenes, J, Romance, M, Sendina-Nadal, I, Wang, Z and Zanin, M (2014) The structure and dynamics of multilayer networks. Physics Reports 544, 1–122.CrossRefGoogle ScholarPubMed
Böhmelt, Tobias (2010) The effectiveness of tracks of diplomacy strategies in third-party interventions. Journal of Peace Research 47, 167–178.CrossRefGoogle Scholar
Cranmer, SJ and Desmarais, BA (2011) Inferential network analysis with exponential random graph models. Political Analysis 19, 66–86.CrossRefGoogle Scholar
Cranmer, SJ and Desmarais, BA (2016) A critique of dyadic design. International Studies Quarterly 60, 355–362.CrossRefGoogle Scholar
Cranmer, SJ, Desmarais, BA and Kirkland, JH (2012a) Toward a network theory of alliance formation. International Interactions 38, 295–324.CrossRefGoogle Scholar
Cranmer, SJ, Desmarais, BA and Menninga, EJ (2012b) Complex dependencies in the alliance network. Conflict Management and Peace Science 29, 279–313.CrossRefGoogle Scholar
Cranmer, SJ, Heinrich, T and Desmarais, BA (2014) Reciprocity and the structural determinants of the international sanctions network. Social Networks 36, 5–22.CrossRefGoogle Scholar
Cranmer, SJ, Leifeld, P, McClurg, SD and Rolfe, M (2017) Navigating the range of statistical tools for inferential network analysis. American Journal of Political Science 61, 237–251.CrossRefGoogle Scholar
Cunningham, DE and Lemke, D (2013) Combining civil and interstate wars. International Organization 67, 609–627.CrossRefGoogle Scholar
Desmarais, BA and Cranmer, SJ (2012) Statistical mechanics of networks: estimation and uncertainty. Physica A: Statistical Mechanics and its Applications 391, 1865–1876.CrossRefGoogle Scholar
Downs, GW and Rocke, DM (1994) Conflict, agency, and gambling for resurrection: the principal-agent problem goes to war. American Journal of Political Science 38, 362–380.CrossRefGoogle Scholar
Fjelde, H and Nilsson, D (2012) Rebels against rebels: explaining violence between rebel groups. Journal of Conflict Resolution 56, 604–628.CrossRefGoogle Scholar
Gleditsch, KS, Salehyan, I and Schultz, K (2008) Fighting at home, fighting abroad: how civil wars lead to international disputes. Journal of Conflict Resolution 52, 479–506.CrossRefGoogle Scholar
Heaney, MT (2014) Multiplex networks and interest group influence reputation: an exponential random graph model. Social Networks 36, 66–81.CrossRefGoogle Scholar
Heaney, MT and Leifeld, P (2018) Contributions by interest groups to lobbying coalitions. Journal of Politics 80, 494–509.CrossRefGoogle Scholar
Hollway, J and Koskinen, J (2016) Multilevel embeddedness: the case of the global fisheries governance complex. Social Networks 44, 281–294.CrossRefGoogle Scholar
Jaber, H (1997) Hezbollah: Born with a Vengeance. New York: Columbia University Press.Google Scholar
Kalyvas, SN and Balcells, L (2010) International system and technologies of rebellion: how the end of the Cold War shaped internal conflict. American Political Science Review 104, 415–429.CrossRefGoogle Scholar
Keck, ME and Sikkink, K (1998) Activists Beyond Borders: Advocacy Networks in International Politics. New York: Cornell University Press.Google Scholar
Keohane, RO (2009) The old IPE and the new. Review of International Political Economy 16, 34–46.CrossRefGoogle Scholar
Kivelä, M, Arenas, A, Barthelemy, M, Gleeson, JP, Moreno, Y and Porter, MA (2014) Multilayer networks. Journal of Complex Networks 2, 203–271.CrossRefGoogle Scholar
Lazer, D (2011) Networks in political science: back to the future. PS: Political Science & Politics 44, 61–68.Google Scholar
Leifeld, P and Fisher, DR (2017) Membership nominations in international scientific assessments. Nature Climate Change 7, 730.CrossRefGoogle Scholar
Leifeld, P and Schneider, V (2012) Information exchange in policy networks. American Journal of Political Science 56, 731–744.CrossRefGoogle Scholar
Luft, G (2000) Israel's security zone in Lebanon-A tragedy? Middle East Quarterly 7, 13–20.Google Scholar
Lusher, D, Koskinen, J and Robins, G (2013) Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications. Cambridge: Cambridge University Press.Google Scholar
Martinez Machain, C and Rosenberg, L (2018) Domestic diversion and strategic behavior by minority groups. Conflict Management and Peace Science 35, 427–450.CrossRefGoogle Scholar
Montgomery, JM and Nyhan, B (2017) The effects of congressional staff networks in the US house of representatives. The Journal of Politics 79, 745–761.CrossRefGoogle Scholar
Nye, JS and Keohane, RO (1971) Transnational relations and world politics: an introduction. International Organization 25, 329–349.CrossRefGoogle Scholar
Robins, G, Snijders, T, Wang, P, Handcock, M and Pattison, P (2007) Recent developments in exponential random graph (p*) models for social networks. Social networks 29, 192–215.CrossRefGoogle Scholar
Snijders, TAB, Pattison, PE, Robins, GL and Handcock, MS (2006) New specifications for exponential random graph models. Sociological Methodology 36, 99–153.CrossRefGoogle Scholar
Song, H (2014) Uncovering the structural underpinnings of political discussion networks: evidence from an exponential random graph model. Journal of Communication 65, 146–169.CrossRefGoogle Scholar
Starr, H (1994) Revolution and war: rethinking the linkage between internal and external conflict. Political Research Quarterly 47, 481–507.CrossRefGoogle Scholar
Tir, J and Jasinski, M (2008) Domestic-level diversionary theory of war: targeting ethnic minorities. Journal of Conflict Resolution 52, 641–664.CrossRefGoogle Scholar
Wang, P, Robins, G, Pattison, P and Lazega, E (2013) Exponential random graph models for multilevel networks. Social Networks 35, 96–115.CrossRefGoogle Scholar
Wang, P, Robins, G, Pattison, P and Lazega, E (2016) Social selection models for multilevel networks. Social Networks 44, 346–362.CrossRefGoogle Scholar
Windzio, M (2018) The network of global migration 1990–2013: using ERGMs to test theories of migration between countries. Social Networks 53, 20–29.CrossRefGoogle Scholar
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