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Bäck, Hanna Debus, Marc and Müller, Wolfgang C. 2016. Intra-party diversity and ministerial selection in coalition governments. Public Choice, Vol. 166, Issue. 3-4, p. 355.
Narayanan, Arthi K. Harding, John D. Saba, Shaddy K. Conley, James and Gordon, Adam J. 2016. Left, right, and meeting in the middle: Addressing addiction is something we can agree about. Substance Abuse, Vol. 37, Issue. 4, p. 495.
Stuckler, David Reeves, Aaron Loopstra, Rachel and McKee, Martin 2016. Textual analysis of sugar industry influence on the World Health Organization’s 2015 sugars intake guideline. Bulletin of the World Health Organization, Vol. 94, Issue. 8, p. 566.
Klingelhöfer, Tristan and Müller, Jochen 2015. Consociational and rational coalitions: Norm-based government formation and the case of the Dutch provinces. Acta Politica, Vol. 50, Issue. 1, p. 101.
Warwick, Paul V. 2015. Public opinion and government policy in Britain: A case of congruence, amplification or dampening?. European Journal of Political Research, Vol. 54, Issue. 1, p. 61.
Collette, Benôit and Pétry, François 2014. From Text to Political Positions.
Costa, Hélia Gilmore, Anna B Peeters, Silvy McKee, Martin and Stuckler, David 2014. Quantifying the influence of the tobacco industry on EU governance: automated content analysis of the EU Tobacco Products Directive. Tobacco Control, Vol. 23, Issue. 6, p. 473.
Krouwel, André and van Elfrinkhof, Annemarie 2014. Combining strengths of methods of party positioning to counter their weaknesses: the development of a new methodology to calibrate parties on issues and ideological dimensions. Quality & Quantity, Vol. 48, Issue. 3, p. 1455.
Grimmer, J. and Stewart, B. M. 2013. Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Political Analysis, Vol. 21, Issue. 3, p. 267.
Müller, Jochen 2013. On a Short Leash? Sub-National Party Positions between Regional Context and National Party Unity. Journal of Elections, Public Opinion & Parties, Vol. 23, Issue. 2, p. 177.
Ruedin, Didier 2013. Obtaining Party Positions on Immigration in Switzerland: Comparing Different Methods. Swiss Political Science Review, Vol. 19, Issue. 1, p. 84.
2012. Multimedia Information Extraction.
Baek, Young Min Cappella, Joseph N. and Bindman, Alyssa 2011. Automating Content Analysis of Open-Ended Responses:WordscoresandAffective Intonation. Communication Methods and Measures, Vol. 5, Issue. 4, p. 275.
Casado-Asensio, Juan and Lefkofridi, Zoe 2011. Representation in the European Union: Congruence Between Citizens and Elites in the European Parliament's Two-Level Setting. Perspectives on European Politics and Society, Vol. 12, Issue. 2, p. 161.
Chen, Yu-Wen 2011. Quantitative Content Analysis of Chinese Texts?: A Methodological Note. Journal of Chinese Political Science, Vol. 16, Issue. 4, p. 431.
Coffé, Hilde and Da Roit, Barbara 2011. Party policy positions in Italy after pre-electoral coalition disintegration. Acta Politica, Vol. 46, Issue. 1, p. 25.
Coffey, Daniel J. 2011. More than a Dime's Worth: Using State Party Platforms to Assess the Degree of American Party Polarization. PS: Political Science & Politics, Vol. 44, Issue. 02, p. 331.
LOWE, WILL BENOIT, KENNETH MIKHAYLOV, SLAVA and LAVER, MICHAEL 2011. Scaling Policy Preferences from Coded Political Texts. Legislative Studies Quarterly, Vol. 36, Issue. 1, p. 123.
Proksch, Sven-Oliver and Slapin, Jonathan B. 2010. Position Taking in European Parliament Speeches. British Journal of Political Science, Vol. 40, Issue. 03, p. 587.
In a recent article in the American Political Science Review, Laver, Benoit, and Garry (2003, “Extracting policy positions from political texts using words as data,” 97:311—331) propose a new method for conducting content analysis. Their Wordscores approach, by automating text-coding procedures, represents an advance in content analysis that will potentially have a large long-term impact on research across the discipline. To allow substantive interpretation, the scores produced by the Wordscores procedure require transformation. In this note, we address several shortcomings in the transformation procedure introduced in the original program. We demonstrate that the original transformation distorts the metric on which content scores are placed—hindering the ability of scholars to make meaningful comparisons across texts—and that it is very sensitive to the texts that are scored—opening up the possibility that researchers may generate, inadvertently or not, results that depend on the texts they choose to include in their analyses. We propose a transformation procedure that solves these problems.
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