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

Bibliographic Data

ID7971076
AuthorsDerek Greene (0000-0001-8065-5418, University College Dublin), James P Cro (0000-0001-8042-1099, University College Dublin), James P Cross
Year2017
Volume25
Issue1
Pages77-94
Publication date2017-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePolitical Analysis (JOURNAL)
Journal identifiersISSN: 1047-1987 • E-ISSN: 1476-4989
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/pan.2016.7
OpenAlexW2460078230
LanguageEN
Citations received52
References cited28

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

Legislature · Parliament · Political economy · Political science · Politics · Sociology · Treaty · Voting · Computational and Text Analysis Methods · Electoral Systems and Political Participation · Law · Political Influence and Corporate Strategies · Public Administration

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Unique citing works52
Citations per year6,5
Citation span2018 - 2026 (9)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 52
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