Comparing computational and non-computational methods in party position estimation: Finland, 2003–2019

5Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

It is often claimed that computational methods for examining textual data give good enough party position estimates at a fraction of the costs of many non-computational methods. However, the conclusive testing of these claims is still far from fully accomplished. We compare the performance of two computational methods, Wordscores and Wordfish, and four non-computational methods in estimating the political positions of parties in two dimensions, a left-right dimension and a progressive-conservative dimension. Our data comprise electoral party manifestos written in Finnish and published in Finland. The non-computational estimates are composed of the Chapel Hill Expert Survey estimates, the Manifesto Project estimates, estimates deriving from survey-based data on voter perceptions of party positions, and estimates derived from electoral candidates’ replies to voting advice application questions. Unlike Wordfish, Wordscores generates relatively well-performing estimates for many of the party positions, but despite this does not offer an even match to the non-computational methods.

Cite

CITATION STYLE

APA

Koljonen, J., Isotalo, V., Ahonen, P., & Mattila, M. (2022). Comparing computational and non-computational methods in party position estimation: Finland, 2003–2019. Party Politics, 28(2), 306–317. https://doi.org/10.1177/1354068820974609

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free