Abstract
Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads of state or government in the United Nations General Debate. The paper provides three key contributions based on the output of the Word2vec model. First, it presents a set of policy attention indices, synthesizing the semantic proximity of political speeches to specific policy themes. Second, it introduces country-specific semantic centrality indices, based on topological analyses of countries' semantic positions with respect to each other. Third, it tests the hypothesis that there exists a statistical relation between the semantic content of political speeches and UN voting behavior, falsifying it and suggesting that political speeches contain information of different nature then the one behind voting outcomes. The paper concludes with a discussion of the practical use of its results and consequences for foreign policy analysis, public accountability, and transparency.
Original language | English |
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Title of host publication | Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 74-79 |
Number of pages | 6 |
ISBN (Electronic) | 9781538631485 |
DOIs | |
Publication status | Published - 1 Jul 2017 |
Event | 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 - Xian, China Duration: 23 Oct 2017 → 25 Oct 2017 |
Publication series
Name | Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
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Volume | 2018-January |
Conference
Conference | 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017 |
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Country/Territory | China |
City | Xian |
Period | 23/10/17 → 25/10/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Information Systems
- Signal Processing
- Software
- Safety, Risk, Reliability and Quality
- Computer Science Applications