Sammenlign metoder

	IGO Network Analysis	Trade Network Analysis
Fagområde	International Relations	International Relations
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	2004	2013
Ophavsperson	Correlates of War IGO data (Pevehouse, Nordstrom & Warnke); network treatments by Ingram, Robinson & Busch and others	Network science applied to trade (e.g., Michael Ward, John Ahlquist & Arturas Rozenas)
Type	Affiliation/co-membership network analysis of international organizations	Network and inferential-network analysis of trade flows
Oprindelig kilde	Pevehouse, J. C., Nordstrom, T., & Warnke, K. (2004). The Correlates of War 2 international governmental organizations data version 2.0. Conflict Management and Peace Science, 21(2), 101–119.	Ward, M. D., Ahlquist, J. S., & Rozenas, A. (2013). Gravity's rainbow: A dynamic latent space model for the world trade network. Network Science, 1(1), 95–118.
Aliasser	Intergovernmental Organization Network Analysis, IGO Co-membership Network, International Organization Network Analysis, IGO Affiliation Network	International Trade Network Analysis, World Trade Web Analysis, Trade Network Topology, Global Trade Graph Analysis
Relaterede	3	3
Resumé	IGO network analysis treats the web of states' memberships in intergovernmental organizations as a network and studies its structure and consequences. Using membership data such as the Correlates of War IGO dataset (Pevehouse, Nordstrom, and Warnke 2004), it represents which states belong to which organizations as an affiliation network, projects it into a state-to-state graph of shared memberships, and analyzes how organizational ties bind states together — measuring integration into global governance, detecting institutional blocs, and testing whether shared IGO membership shapes outcomes like trade and conflict.	Trade network analysis studies international trade as a weighted, directed graph in which states are nodes and trade flows are edges, then characterizes its structure and models how ties form. It moves beyond the standard dyadic gravity model by treating trade relationships as interdependent — a state's trade with one partner depends on the wider web of trade — and uses network science and inferential models such as latent space models (Ward, Ahlquist, and Rozenas 2013) to capture this dependence, identify hubs and blocs, and explain the architecture of the world trade system.