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The Manifesto Corpus: A new resource for research on political parties and quantitative text analysis

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  • Merz, Nicolas
  • Regel, Sven
  • Lewandowski, Jirka

Abstract

This article presents a digital, open-access, multilingual, annotated corpus of electoral programs. It complements the recent methodological innovations in (semi-) computerized content analysis by providing a large, standardized text corpus for the political science community. The corpus is based on the collection of the Manifesto Project, which comprises of (at the time of writing) the largest hand-annotated text corpus of electoral programs available. Since 2009 the project’s costly and time-intensive procedure of collecting and coding documents has been fully digitized. As a result, it now provides more than 1800 machine readable documents from 40 different countries. Six hundred of these documents contain content-analyzed annotations at the level of single (quasi-) sentences, which correspond to the Manifesto Project coding scheme. Additionally, the corpus will continually be extended by incorporating new elections and digitizing older documents. The database also provides meta-information for each document (eg. party, election, language, etc.) that allow it to be referenced back to the Manifesto Dataset. The corpus is stored in a standardized format in an online database, and an API and R package (manifestoR) guarantee easy access.

Suggested Citation

  • Merz, Nicolas & Regel, Sven & Lewandowski, Jirka, 2016. "The Manifesto Corpus: A new resource for research on political parties and quantitative text analysis," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(2 (April-), pages 1-8.
  • Handle: RePEc:zbw:espost:172197
    DOI: 10.1177/2053168016643346
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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.
    3. John Wilkerson & David Smith & Nicholas Stramp, 2015. "Tracing the Flow of Policy Ideas in Legislatures: A Text Reuse Approach," American Journal of Political Science, John Wiley & Sons, vol. 59(4), pages 943-956, October.
    4. Mattia Zulianello, 2014. "Analyzing party competition through the comparative manifesto data: some theoretical and methodological considerations," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1723-1737, May.
    5. Däubler, Thomas & Benoit, Kenneth & Mikhaylov, Slava & Laver, Michael, 2012. "Natural Sentences as Valid Units for Coded Political Texts," British Journal of Political Science, Cambridge University Press, vol. 42(4), pages 937-951, October.
    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. 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. Jonathan B. Slapin & Sven‐Oliver Proksch, 2008. "A Scaling Model for Estimating Time‐Series Party Positions from Texts," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 705-722, July.
    9. 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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    Cited by:

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    2. Nicolas Gavoille & Katharina Hofer, 2021. "Capital Controls and Electoral Cycles," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(2), pages 275-324, June.
    3. Carlos Bianchi & Camilo Martínez, 2023. "STI policy conventions in Uruguay. An analysis of political party platforms 2004–2019," Review of Policy Research, Policy Studies Organization, vol. 40(2), pages 260-281, March.
    4. Karim Bekhtiar, 2023. "The decline of manufacturing employment and the rise of the far-right in Austria," Economics working papers 2023-09, Department of Economics, Johannes Kepler University Linz, Austria.
    5. Valerio Leone Sciabolazza, 2022. "Bargaining within the Council of the European Union: An Empirical Study on the Allocation of Funds of the European Budget," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(2), pages 227-258, July.
    6. Caroline Le Pennec, 2024. "Strategic Campaign Communication: Evidence from 30,000 Candidate Manifestos," The Economic Journal, Royal Economic Society, vol. 134(658), pages 785-810.
    7. Lance Y. Hunter & Joseph W. Robbins & Martha H. Ginn & Aaron Hutton, 2019. "Meet in the Middle: Terrorism and Centrist Party Vote Shares in Legislative Elections," Global Policy, London School of Economics and Political Science, vol. 10(1), pages 60-74, February.
    8. Rauh, Christian, 2018. "Validating a sentiment dictionary for German political language—a workbench note," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(4), pages 319-343.
    9. Zobel, Malisa & Lehmann, Pola, 2018. "Positions and saliency of immigration in party manifestos: A novel dataset using crowd coding," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 57(4), pages 1056-1083.

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