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Finding the structure of parliamentary motions in the Swedish Riksdag 1971–2015

Author

Listed:
  • Bastiaan Bruinsma

    (Chalmers University of Technology)

  • Moa Johansson

    (Chalmers University of Technology)

Abstract

The current increase in the number of large, open sets of unstructured textual data has created both opportunities and challenges for social scientists. Here, we explore if and how we can use such data by looking at a dataset of over 144,000 documents used by parliamentary committees in Sweden. Of these, we aim to understand: (a) the topical content of these motions, (b) how these topics have changed over time, and (c) how these topics differ across political parties. To do so, we use a Structural Topic Model, which allows us to not only find the topics using the textual data itself, but also to include the documents’ metadata, such as authorship and date of publication. Doing so, we find 30 topics, which we combine into 9 broader themes. We find that these themes often rise and fall in popularity in line with historical events, and relate to the various political parties as we would expect. Throughout our analysis, we provide a step-by-step overview of how to use structural topic models in practice and also how to handle the type of dataset we use here.

Suggested Citation

  • Bastiaan Bruinsma & Moa Johansson, 2024. "Finding the structure of parliamentary motions in the Swedish Riksdag 1971–2015," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3275-3301, August.
    • Handle: RePEc:spr:qualqt:v:58:y:2024:i:4:d:10.1007_s11135-023-01802-9
    DOI: 10.1007/s11135-023-01802-9
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    References listed on IDEAS

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    1. Hobolt, Sara B. & Wratil, Christopher, 2015. "Public opinion and the crisis: the dynamics of support for the euro," LSE Research Online Documents on Economics 60788, London School of Economics and Political Science, LSE Library.
    2. 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.
    3. 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.
    4. Greene, Zac & Ceron, Andrea & Schumacher, Gijs & Fazekas, Zoltan, 2016. "The Nuts and Bolts of Automated Text Analysis. Comparing Different Document Pre-Processing Techniques in Four Countries," OSF Preprints ghxj8, Center for Open Science.
    5. Carling, Kenneth & Richardson, Katarina, 2004. "The relative efficiency of labor market programs: Swedish experience from the 1990s," Labour Economics, Elsevier, vol. 11(3), pages 335-354, June.
    6. 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.
    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.
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