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How to Measure Agreement, Consensus, and Polarization in Ordinal Data

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  • Aeppli, Clem
  • Ruedin, Didier

    (University of Neuchâtel)

Abstract

Different measures exist to capture agreement, consensus, concentration, dispersion, and polarization in ordinal data. We compare consensus scores across specific situations for a better understanding of how different measures work in practice: constructed cases, simulated data where we know the underlying distribution, and empirical data. Although researchers have solved the ‘problem’ of measuring agreement, consensus, and polarization several times, we highlight similarities and equivalence across some existing approaches, while others differ substantially. The choice of method can lead to substantively different conclusions, and we recommend that researchers use a combination of measures and use graphics to examine the distribution qualitatively.

Suggested Citation

  • Aeppli, Clem & Ruedin, Didier, 2022. "How to Measure Agreement, Consensus, and Polarization in Ordinal Data," SocArXiv syzbr, Center for Open Science.
    • Handle: RePEc:osf:socarx:syzbr
    DOI: 10.31219/osf.io/syzbr
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    References listed on IDEAS

    as
    1. Cees Van Der Eijk, 2001. "Measuring Agreement in Ordered Rating Scales," Quality & Quantity: International Journal of Methodology, Springer, vol. 35(3), pages 325-341, August.
    2. João Carvalho & Mariana Carmo Duarte, 2020. "The Politicization of Immigration in Portugal between 1995 and 2014: A European Exception?," Journal of Common Market Studies, Wiley Blackwell, vol. 58(6), pages 1469-1487, November.
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