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Measuring and Explaining Political Sophistication through Textual Complexity

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  • Kenneth Benoit
  • Kevin Munger
  • Arthur Spirling

Abstract

Political scientists lack domain‐specific measures for the purpose of measuring the sophistication of political communication. We systematically review the shortcomings of existing approaches, before developing a new and better method along with software tools to apply it. We use crowdsourcing to perform thousands of pairwise comparisons of text snippets and incorporate these results into a statistical model of sophistication. This includes previously excluded features such as parts of speech and a measure of word rarity derived from dynamic term frequencies in the Google Books data set. Our technique not only shows which features are appropriate to the political domain and how, but also provides a measure easily applied and rescaled to political texts in a way that facilitates probabilistic comparisons. We reanalyze the State of the Union corpus to demonstrate how conclusions differ when using our improved approach, including the ability to compare complexity as a function of covariates.

Suggested Citation

  • Kenneth Benoit & Kevin Munger & Arthur Spirling, 2019. "Measuring and Explaining Political Sophistication through Textual Complexity," American Journal of Political Science, John Wiley & Sons, vol. 63(2), pages 491-508, April.
    • Handle: RePEc:wly:amposc:v:63:y:2019:i:2:p:491-508
    DOI: 10.1111/ajps.12423
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    References listed on IDEAS

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    1. Turner, Heather & Firth, David, 2012. "Bradley-Terry Models in R: The BradleyTerry2 Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i09).
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    2. Amarasinghe, Ashani, 2022. "Diverting domestic turmoil," Journal of Public Economics, Elsevier, vol. 208(C).
    3. Hamza Bennani & Matthias Neuenkirch, 2022. "Too Complex to Digest? Federal Tax Bills and Their Processing in US Financial Markets," CESifo Working Paper Series 10052, CESifo.
    4. Rebecca Cordell & Kristian Skrede Gleditsch & Florian G Kern & Laura Saavedra-Lux, 2020. "Measuring institutional variation across American Indian constitutions using automated content analysis," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 777-788, November.
    5. Ferrara, Federico Maria & Angino, Siria, 2022. "Does clarity make central banks more engaging? Lessons from ECB communications," European Journal of Political Economy, Elsevier, vol. 74(C).
    6. Özdemir, Sina & Rauh, Christian, 2022. "A Bird’s Eye View: Supranational EU Actors on Twitter," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(1), pages 133-145.
    7. Gloria Gennaro & Elliott Ash, 2022. "Emotion and Reason in Political Language," The Economic Journal, Royal Economic Society, vol. 132(643), pages 1037-1059.
    8. Rauh, Christian, 2022. "Clear messages to the European public? The language of European Commission press releases 1985–2020," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest Ar, pages 1-19.
    9. Adam M. Samaha & Michael Heise & Gregory C. Sisk, 2020. "Inputs and Outputs on Appeal: An Empirical Study of Briefs, Big Law, and Case Complexity," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(3), pages 519-555, September.
    10. Sina Özdemir & Christian Rauh, 2022. "A Bird’s Eye View: Supranational EU Actors on Twitter," Politics and Governance, Cogitatio Press, vol. 10(1), pages 133-145.
    11. Eddy Cardinaels & Christoph Feichter, 2021. "Forced Rating Systems from Employee and Supervisor Perspectives," Journal of Accounting Research, Wiley Blackwell, vol. 59(5), pages 1573-1607, December.

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