Baturo, Alexander ORCID: 0000-0002-1108-5287 and Dasandi, Niheer ORCID: 0000-0002-8708-837X (2018) What drives the international development agenda? An NLP analysis of the United Nations General Debate 1970-2016. In: International Conference on the Frontiers and Advances in Data Science (FADS), 23-25 Oct. 2017, Xi'an, China.
Abstract
Surprisingly little is known about agenda setting for
international development in the United Nations (UN), despite
it having a significant influence on the process and outcomes
of development efforts. This paper addresses this shortcoming
using a novel approach that applies natural language processing
techniques to countries’ annual statements in the UN General
Debate. Every year UN member states deliver statements during
the General Debate on their governments’ perspective on major
issues in world politics. These speeches provide invaluable information on state preferences on a wide range of issues, including
international development, but have largely been overlooked in
the study of global politics. This paper identifies the main international development topics that states raise in these speeches
between 1970 and 2016, and examine the country-specific drivers
of international development rhetoric.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Government; Coherence; Semantics; Economics; Security; Speech; Biological system modeling |
Subjects: | Social Sciences > International relations Social Sciences > Political science |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Law and Government |
Published in: | International Conference on the Frontiers and Advances in Data Science (FADS),Proceedings of. . IEEE. |
Publisher: | IEEE |
Official URL: | https://dx.doi.org/10.1109/FADS.2017.8253221 |
Copyright Information: | © 2017 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 25595 |
Deposited On: | 08 Mar 2021 16:02 by Thomas Murtagh . Last Modified 08 Mar 2021 16:02 |
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