Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus
July 10, 2017 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Alexander Baturo, Niheer Dasandi, Slava J. Mikhaylov
arXiv ID
1707.02774
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
stat.ML
Citations
168
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Every year at the United Nations, member states deliver statements during the General Debate discussing major issues in world politics. These speeches provide invaluable information on governments' perspectives and preferences on a wide range of issues, but have largely been overlooked in the study of international politics. This paper introduces a new dataset consisting of over 7,701 English-language country statements from 1970-2016. We demonstrate how the UN General Debate Corpus (UNGDC) can be used to derive country positions on different policy dimensions using text analytic methods. The paper provides applications of these estimates, demonstrating the contribution the UNGDC can make to the study of international politics.
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