Proximity Based Circular Visualization for Similarity Analysis of UNGA Voting Patterns

In this paper, we present interactive visualization methods that analyze the relations between nations from UN General Assembly (UNGA) voting data. Our methods visualize the relations in several aspects such as specific issues or time period. UNGA voting data contains of 5211 resolutions from 1946 to 2012. For this work, we designed a similarity, metrics between nations and developed two different visualization method-based similarity metrics. The first one is Network Graph Visualization which identifies the relations between nations, applying the voting result of annual United Nations General Assembly resolutions with Social network graph. Next, Proximity based Circular Visualization illustrates relations between the nations focusing on a specific country, or changes in the voting pattern between nations in a sequential manner. As a research result, we discovered that Proximity based Circular Visualization would lead to better analysis when focusing on individual nodes, whereas Network Graph Visualization brings more distinct results on the similarity pattern between countries.