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  5. Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach
 
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Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach

Author(s)
Greene, Derek  
Cross, James P.  
Uri
http://hdl.handle.net/10197/8690
Date Issued
2017-01
Date Available
2017-07-27T10:08:33Z
Abstract
This study analyzes the political agenda of the European Parliament (EP) plenary, how it has evolved over time, and the manner in which Members of the European Parliament (MEPs) have reacted to external and internal stimuli when making plenary speeches. To unveil the plenary agenda and detect latent themes in legislative speeches over time, MEP speech content is analyzed using a new dynamic topic modeling method based on two layers of Non-negative Matrix Factorization (NMF). This method is applied to a new corpus of all English language legislative speeches in the EP plenary from the period 1999 to 2014. Our findings suggest that two-layer NMF is a valuable alternative to existing dynamic topic modeling approaches found in the literature, and can unveil niche topics and associated vocabularies not captured by existing methods. Substantively, our findings suggest that the political agenda of the EP evolves significantly over time and reacts to exogenous events such as EU Treaty referenda and the emergence of the Euro Crisis. MEP contributions to the plenary agenda are also found to be impacted upon by voting behavior and the committee structure of the Parliament.
Sponsorship
Irish Research Council
Science Foundation Ireland
Type of Material
Journal Article
Publisher
Cambridge University Press
Journal
Political Analysis
Volume
25
Issue
1
Start Page
77
End Page
94
Copyright (Published Version)
2017 the Authors
Subjects

Machine learning

Statistics

DOI
10.1017/pan.2016.7
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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insight_publication.pdf

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463.84 KB

Format

Adobe PDF

Checksum (MD5)

9bf148ff36b7723a90deadd6de42ca51

Owning collection
Insight Research Collection
Mapped collections
Computer Science Research Collection•
Politics and International Relations Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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