Qualitative analysis for big data: tidytext and topicmodels
Year: 2025
Type: preprint
Abstract: Quantitative researchers in psychology often collect big data with open-ended text responses, but they may not know how to analyze or interpret these data qualitatively. Qualitative researchers in psychology know how to analyze text responses but the burden of manual coding for big data can be unbearable. This tutorial shows how to use packages in R (tidytext and topicmodels) as computer-assisted qualitative data analysis software (CAQDAS) tools. We describe the process for analyzing large-scale open-text data, especially for quantitative psychologists who want to make better use of open-ended data and incorporate qualitative techniques. Qualitative researchers can similarly use this tutorial to more easily synthesize and organize large quantities of responses. Using an open-source dataset, we demonstrate and discuss the basic steps needed to conduct similar analyses on researchers’ own data. By making qualitative analysis accessible to quantitative researchers, and open-source software procedures accessible to qualitative researchers, we hope to spur more cross-training and collaboration across self-described quantitative and qualitative researchers.
Authors: Eleanor J Junkins, Jaime Derringer
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4407367249