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What’s the talk in Brussels? Leveraging daily news coverage to measure issue attention in the European Union

Author

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  • Michal Ovádek

    (Centre for Legal Theory and Empirical Jurisprudence, KU Leuven, Leuven, Belgium)

  • Nicolas Lampach

    (Centre for Legal Theory and Empirical Jurisprudence, KU Leuven, Leuven, Belgium)

  • Arthur Dyevre

    (Centre for Legal Theory and Empirical Jurisprudence, KU Leuven, Leuven, Belgium)

Abstract

Research on issue attention in the European Union has focused on the prominence of EU integration in domestic politics and media and, at EU level, on the salience of individual issues and legislative files, often in relation to lobbying. Existing EU-level measures of issue saliency, though, are limited in scope and periodicity and tend to reflect the policy priorities of a single institutional actor rather than that of the broader EU elite sphere. We present an alternative measure of issue attention leveraging the quasi-institutional nature of the Agence Europe daily bulletin which provides comprehensive but independent news coverage of EU affairs. We use text-mining techniques, including dynamic topic modelling, in combination with manual classification to map issue prevalence between 1979 and 2018. In addition to reporting validation results, we illustrate how our measure relates to other indicators of EU agenda formation and explain how researchers can make use of our new dataset.

Suggested Citation

  • Michal Ovádek & Nicolas Lampach & Arthur Dyevre, 2020. "What’s the talk in Brussels? Leveraging daily news coverage to measure issue attention in the European Union," European Union Politics, , vol. 21(2), pages 204-232, June.
    • Handle: RePEc:sae:eeupol:v:21:y:2020:i:2:p:204-232
    DOI: 10.1177/1465116520902530
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    References listed on IDEAS

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    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Grimmer, Justin, 2010. "A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases," Political Analysis, Cambridge University Press, vol. 18(1), pages 1-35, January.
    3. Denny, Matthew J. & Spirling, Arthur, 2018. "Text Preprocessing For Unsupervised Learning: Why It Matters, When It Misleads, And What To Do About It," Political Analysis, Cambridge University Press, vol. 26(2), pages 168-189, April.
    4. Greene, Derek & Cross, James P., 2017. "Exploring the Political Agenda of the European Parliament Using a Dynamic Topic Modeling Approach," Political Analysis, Cambridge University Press, vol. 25(1), pages 77-94, January.
    5. Kim, Sung Eun, 2018. "Media Bias against Foreign Firms as a Veiled Trade Barrier: Evidence from Chinese Newspapers," American Political Science Review, Cambridge University Press, vol. 112(4), pages 954-970, November.
    6. Arghyrou, Michael G. & Kontonikas, Alexandros, 2012. "The EMU sovereign-debt crisis: Fundamentals, expectations and contagion," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 658-677.
    7. Lucas, Christopher & Nielsen, Richard A. & Roberts, Margaret E. & Stewart, Brandon M. & Storer, Alex & Tingley, Dustin, 2015. "Computer-Assisted Text Analysis for Comparative Politics," Political Analysis, Cambridge University Press, vol. 23(2), pages 254-277, April.
    8. Dybowski, T.P. & Adämmer, P., 2018. "The economic effects of U.S. presidential tax communication: Evidence from a correlated topic model," European Journal of Political Economy, Elsevier, vol. 55(C), pages 511-525.
    9. Radoslav S. Dimitrov, 2010. "Inside Copenhagen: The State of Climate Governance," Global Environmental Politics, MIT Press, vol. 10(2), pages 18-24, May.
    10. Marcello Carammia & Sebastiaan Princen & Arco Timmermans, 2016. "From Summitry to EU Government: An Agenda Formation Perspective on the European Council," Journal of Common Market Studies, Wiley Blackwell, vol. 54(4), pages 809-825, July.
    11. Simone Manganelli & Guido Wolswijk, 2009. "What drives spreads in the euro area government bond market? [‘What “hides” behind sovereign debt ratings?’]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 24(58), pages 191-240.
    12. Sorace, Miriam, 2018. "The European Union democratic deficit: substantive representation in the European Parliament at the input stage," LSE Research Online Documents on Economics 87625, London School of Economics and Political Science, LSE Library.
    13. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    14. Kevin M. Quinn & Burt L. Monroe & Michael Colaresi & Michael H. Crespin & Dragomir R. Radev, 2010. "How to Analyze Political Attention with Minimal Assumptions and Costs," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 209-228, January.
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    1. Laurer, Moritz & Seidl, Timo, 2020. "Regulating the European Data-Driven Economy. A Case Study on the General Data Protection Regulation," SocArXiv a6m8r, Center for Open Science.

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