Computers, coders, and voters: Comparing automated methods for estimating party positions

Assigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against exp...

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Main Authors: Frederik Hjorth, Robert Klemmensen, Sara Hobolt, Martin Ejnar Hansen, Peter Kurrild-Klitgaard
Format: Article
Language:English
Published: SAGE Publishing 2015-04-01
Series:Research & Politics
Online Access:https://doi.org/10.1177/2053168015580476
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spelling doaj-ec80d18aaacc43f89b0a4c8b17b5ed1a2020-11-25T02:53:59ZengSAGE PublishingResearch & Politics2053-16802015-04-01210.1177/205316801558047610.1177_2053168015580476Computers, coders, and voters: Comparing automated methods for estimating party positionsFrederik Hjorth0Robert Klemmensen1Sara Hobolt2Martin Ejnar Hansen3Peter Kurrild-Klitgaard4University of Copenhagen, DenmarkUniversity of Southern Denmark, DenmarkLondon School of Economics, UKBrunel University, UKUniversity of Copenhagen, DenmarkAssigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against expert placements. We estimate the positions of 254 manifestos across 33 elections in Germany and Denmark, two cases with very different textual data available. We find that Wordscores approximately replicates the CMP, voter, and expert assessments of party positions in both cases, whereas Wordfish replicates the positions in the German manifestos only. The results demonstrate that automated methods can produce valid estimates of party positions, but also that the appropriateness of each method hinges on the quality of the textual data. Additional analyses suggest that Wordfish requires both longer texts and a more ideologically charged vocabulary in order to produce estimates comparable to Wordscores. The paper contributes to the literature on automated content analysis by providing a comprehensive test of convergent validation, in terms of both number of cases analyzed and number of validation measures.https://doi.org/10.1177/2053168015580476
collection DOAJ
language English
format Article
sources DOAJ
author Frederik Hjorth
Robert Klemmensen
Sara Hobolt
Martin Ejnar Hansen
Peter Kurrild-Klitgaard
spellingShingle Frederik Hjorth
Robert Klemmensen
Sara Hobolt
Martin Ejnar Hansen
Peter Kurrild-Klitgaard
Computers, coders, and voters: Comparing automated methods for estimating party positions
Research & Politics
author_facet Frederik Hjorth
Robert Klemmensen
Sara Hobolt
Martin Ejnar Hansen
Peter Kurrild-Klitgaard
author_sort Frederik Hjorth
title Computers, coders, and voters: Comparing automated methods for estimating party positions
title_short Computers, coders, and voters: Comparing automated methods for estimating party positions
title_full Computers, coders, and voters: Comparing automated methods for estimating party positions
title_fullStr Computers, coders, and voters: Comparing automated methods for estimating party positions
title_full_unstemmed Computers, coders, and voters: Comparing automated methods for estimating party positions
title_sort computers, coders, and voters: comparing automated methods for estimating party positions
publisher SAGE Publishing
series Research & Politics
issn 2053-1680
publishDate 2015-04-01
description Assigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against expert placements. We estimate the positions of 254 manifestos across 33 elections in Germany and Denmark, two cases with very different textual data available. We find that Wordscores approximately replicates the CMP, voter, and expert assessments of party positions in both cases, whereas Wordfish replicates the positions in the German manifestos only. The results demonstrate that automated methods can produce valid estimates of party positions, but also that the appropriateness of each method hinges on the quality of the textual data. Additional analyses suggest that Wordfish requires both longer texts and a more ideologically charged vocabulary in order to produce estimates comparable to Wordscores. The paper contributes to the literature on automated content analysis by providing a comprehensive test of convergent validation, in terms of both number of cases analyzed and number of validation measures.
url https://doi.org/10.1177/2053168015580476
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