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

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 1999-2014. 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 behaviour and the committee structure of the Parliament.

[1]  Sven-Oliver Proksch,et al.  Parliamentary Questions, Oversight, and National Opposition Status in the European Parliament , 2013 .

[2]  Richard A. Harshman,et al.  Indexing by Latent Semantic Analysis , 1990, J. Am. Soc. Inf. Sci..

[3]  David G. Rand,et al.  Structural Topic Models for Open‐Ended Survey Responses , 2014, American Journal of Political Science.

[4]  Joost Berkhout,et al.  The Politics of Attention: How Government Prioritizes Problems , 2008 .

[5]  Derek Greene,et al.  How Many Topics? Stability Analysis for Topic Models , 2014, ECML/PKDD.

[6]  Quan Wang,et al.  Group matrix factorization for scalable topic modeling , 2012, SIGIR '12.

[7]  Justin Grimmer,et al.  A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases , 2010, Political Analysis.

[8]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[9]  J. T. Wulu,et al.  Regression analysis of count data , 2002 .

[10]  Marcello Carammia,et al.  Policy Punctuations and Issue Diversity on the European Council Agenda , 2012 .

[11]  John D. Lafferty,et al.  Dynamic topic models , 2006, ICML.

[12]  D. Farrell,et al.  National or European Parliamentarians? Evidence from a New Survey of the Members of the European Parliament , 2012 .

[13]  Shaun Bevan,et al.  What Are Policy Punctuations? Large Changes in the Legislative Agenda of the UK Government, 1911–2008 , 2012 .

[14]  David M. Blei,et al.  Probabilistic topic models , 2012, Commun. ACM.

[15]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[16]  Christos Boutsidis,et al.  SVD based initialization: A head start for nonnegative matrix factorization , 2008, Pattern Recognit..

[17]  Jonathan B. Slapin,et al.  Position Taking in European Parliament Speeches , 2010 .

[18]  Chih-Jen Lin,et al.  Projected Gradient Methods for Nonnegative Matrix Factorization , 2007, Neural Computation.

[19]  Dragomir R. Radev,et al.  How to Analyze Political Attention with Minimal Assumptions and Costs , 2010 .

[20]  Sven-Oliver Proksch,et al.  The Politics of Parliamentary Debate: Parties, Rebels and Representation , 2014 .

[21]  S. Hix,et al.  Democratic Politics in the European Parliament: Index , 2007 .

[22]  Robert Grossman,et al.  Meaningful selection of temporal resolution for dynamic networks , 2010, MLG '10.

[23]  Will Jennings,et al.  Comparative Political Studies , 1999 .

[24]  Sven-Oliver Proksch,et al.  Look who’s talking: Parliamentary debate in the European Union , 2010 .

[25]  David Buttler,et al.  Exploring Topic Coherence over Many Models and Many Topics , 2012, EMNLP.

[26]  Gérard Roland,et al.  Dimensions of politics in the European Parliament , 2006 .

[27]  Tapio Raunio,et al.  Parliamentary questions in the European parliament: Representation, information and control , 1996 .

[28]  Gérard Roland,et al.  Democratic Politics in the European Parliament: Index , 2007 .

[29]  Derek Greene,et al.  An analysis of the coherence of descriptors in topic modeling , 2015, Expert Syst. Appl..

[30]  Michael Röder,et al.  Exploring the Space of Topic Coherence Measures , 2015, WSDM.

[31]  Bryan D. Jones,et al.  From There to Here: Punctuated Equilibrium to the General Punctuation Thesis to a Theory of Government Information Processing , 2012 .

[32]  Peter John,et al.  Agendas and Instability in American Politics , 2013 .

[33]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[34]  A. Downs.  Up and Down with Ecology--The Issue Attention Cycle , 1972 .

[35]  David M. Farrell,et al.  The Organizing of the European Parliament: Committees, Specialization and Co-ordination , 1995, British Journal of Political Science.

[36]  Shaun Bevan,et al.  What are Policy Punctuations? Large Changes in the Legislative Agenda of the UK Government, 1911-2008 , 2011 .

[37]  Keith Dowding,et al.  The Comparative Policy Agendas Project: theory, measurement and findings* , 2015, Journal of Public Policy.

[38]  Chong Wang,et al.  Reading Tea Leaves: How Humans Interpret Topic Models , 2009, NIPS.

[39]  B. Jones,et al.  Punctuated Equilibrium in Comparative Perspective , 2009 .

[40]  B. Jones.  Reconceiving Decision-Making in Democratic Politics: Attention, Choice, and Public Policy , 1994 .