Computers, Coders, and Voters: Comparing Automated Methods for Estimating Party Positions
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Computers, Coders, and Voters: Comparing Automated Methods for Estimating Party Positions. / Hjorth, Frederik Georg; Klemmensen, Robert Tranekær; Hobolt, Sara Binzer; Hansen, Martin Ejnar; Kurrild-Klitgaard, Peter.
In: Research & Politics, Vol. 2, No. 2, 01.04.2015, p. 1-9.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Computers, Coders, and Voters: Comparing Automated Methods for Estimating Party Positions
AU - Hjorth, Frederik Georg
AU - Klemmensen, Robert Tranekær
AU - Hobolt, Sara Binzer
AU - Hansen, Martin Ejnar
AU - Kurrild-Klitgaard, Peter
PY - 2015/4/1
Y1 - 2015/4/1
N2 - 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.
AB - 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.
KW - Faculty of Social Sciences
KW - Text as data
KW - automated content analysis
KW - party positions
KW - Wordscores
KW - Wordfish
KW - CMP
U2 - 10.1177/2053168015580476
DO - 10.1177/2053168015580476
M3 - Journal article
VL - 2
SP - 1
EP - 9
JO - Research and Politics
JF - Research and Politics
SN - 2053-1680
IS - 2
ER -
ID: 130524567