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The promises of quantitative text analysis in interest group research: A reply to Bunea and Ibenskas

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  • Heike Klüver

Abstract

Quantitative text analysis constitutes a promising new method that allows for measuring the policy positions and the lobbying success of interest groups by analyzing their submissions to legislative consultations ( Klüver, 2009 ). The use of quantitative text analysis allowed me to present a novel and unique research design which was the largest in scope at the time and resulted in important new insights regarding the determinants of lobbying success ( Klüver, 2009 , 2011 , 2013 ). In their recent article, Bunea and Ibenskas (2015) however question the usefulness of quantitative text analysis for studying interest groups and discuss several issues which in their view constitute important disadvantages of the technique. In this article I carefully discuss each of their arguments and show that none of their objections actually prevents scholars from successfully using quantitative text analysis to study interest groups in the European Union and beyond.

Suggested Citation

  • Heike Klüver, 2015. "The promises of quantitative text analysis in interest group research: A reply to Bunea and Ibenskas," European Union Politics, , vol. 16(3), pages 456-466, September.
    • Handle: RePEc:sae:eeupol:v:16:y:2015:i:3:p:456-466
    DOI: 10.1177/1465116515581669
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    References listed on IDEAS

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    1. 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.
    2. Mikhaylov, Slava & Laver, Michael & Benoit, Kenneth R., 2012. "Coder Reliability and Misclassification in the Human Coding of Party Manifestos," Political Analysis, Cambridge University Press, vol. 20(1), pages 78-91, January.
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    4. Proksch, Sven-Oliver & Slapin, Jonathan B., 2010. "Position Taking in European Parliament Speeches," British Journal of Political Science, Cambridge University Press, vol. 40(3), pages 587-611, July.
    5. Klüver, Heike & Mahoney, Christine, 2015. "Measuring interest group framing strategies in public policy debates," Journal of Public Policy, Cambridge University Press, vol. 35(2), pages 223-244, August.
    6. 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.
    7. Hix, Simon & Noury, Abdul & Roland, Gérard, 2005. "Power to the Parties: Cohesion and Competition in the European Parliament, 1979–2001," British Journal of Political Science, Cambridge University Press, vol. 35(2), pages 209-234, April.
    8. Laver, Michael & Benoit, Kenneth & Garry, John, 2003. "Extracting Policy Positions from Political Texts Using Words as Data," American Political Science Review, Cambridge University Press, vol. 97(2), pages 311-331, May.
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