We construct a network of member states of the United Nations General Assembly based on how similarly they vote on resolutions. We describe a similarity metric that we feel better describes the inter-nation relationships than previously proposed models. Next, we introduce a mechanism to infer the best diplomatic path between countries that do not have high similarity in voting. Lastly, we create a bilateral commodity trade network between countries and evaluate the overlap between the trade and voting networks by applying community detection analysis. Our findings show that generated communities mimic real-world groupings and that there indeed is an alignment between voting and trade networks, paving the way for further studies on the connection between economic dependence and voting behavior.
CITATION STYLE
Magu, R., & Mateos, G. (2018). United nations general assembly vote similarity networks. In Studies in Computational Intelligence (Vol. 689, pp. 1174–1183). Springer Verlag. https://doi.org/10.1007/978-3-319-72150-7_95
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