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Topics, Concepts, and Measurement: A Crowdsourced Procedure for Validating Topics as Measures

Published online by Cambridge University Press:  27 September 2021

Luwei Ying*
Affiliation:
Department of Political Science, Washington University in St. Louis, Greater St. Louis, MO, USA. E-mail: luwei.ying@wustl.edu
Jacob M. Montgomery
Affiliation:
Department of Political Science, Washington University in St. Louis, Greater St. Louis, MO, USA. E-mail: jacob.montgomery@wustl.edu
Brandon M. Stewart
Affiliation:
Department of Sociology and the Office of Population Research, Princeton University, Princeton, NJ, USA. E-mail: bms4@princeton.edu
*
Corresponding author Luwei Ying

Abstract

Topic models, as developed in computer science, are effective tools for exploring and summarizing large document collections. When applied in social science research, however, they are commonly used for measurement, a task that requires careful validation to ensure that the model outputs actually capture the desired concept of interest. In this paper, we review current practices for topic validation in the field and show that extensive model validation is increasingly rare, or at least not systematically reported in papers and appendices. To supplement current practices, we refine an existing crowd-sourcing method by Chang and coauthors for validating topic quality and go on to create new procedures for validating conceptual labels provided by the researcher. We illustrate our method with an analysis of Facebook posts by U.S. Senators and provide software and guidance for researchers wishing to validate their own topic models. While tailored, case-specific validation exercises will always be best, we aim to improve standard practices by providing a general-purpose tool to validate topics as measures.

Type
Article
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology

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Footnotes

Edited by Jeff Gill

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Ying et al. supplementary material

Ying et al. supplementary material

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