The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Topic Modeling as a Strategy of Inquiry in Organizational Research: A Tutorial With an Application Example on Organizational Culture
Open accessAbstract
Research has emphasized the limitations of qualitative and quantitative approaches to studying organizational phenomena. For example, in-depth interviews are resource-intensive, while questionnaires with closed-ended questions can only measure predefined constructs. With the recent availability of large textual data sets and increased computational power, text mining has become an attractive method that has the potential to mitigate some of these limitations. Thus, we suggest applying topic modeling, a specific text mining technique, as a new and complementary strategy of inquiry to study organizational phenomena. In particular, we outline the potentials of structural topic modeling for organizational research and provide a step-by-step tutorial on how to apply it. Our application example builds on 428,492 reviews of Fortune 500 companies from the online platform Glassdoor, on which employees can evaluate organizations. We demonstrate how structural topic models allow to inductively identify topics that matter to employees and quantify their relationship with employees’ perception of organizational culture. We discuss the advantages and limitations of topic modeling as a research method and outline how future research can apply the technique to study organizational phenomena.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The creation of our structural topic model follows the protocol described in (Schmiedel et al., 2019) and is supported by the stm package in R (Roberts et al., 2019).”
From Ethical use of artificial intelligence based tools in higher education: Are future business leaders ready? (2025) · cites this paper as Schmiedel et al., 2019
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology
Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013) · Organizational Research Methods · doi:10.1177/1094428112452151 · Cited by 13,227
The Handbook of Social Psychology
Gravatt, A. E., Lindzey, G. E., & Aronson, F. (1969) · The Family Coordinator · doi:10.2307/582242 · Cited by 12,518
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Weber, R. (1990) · doi:10.4135/9781412983488 · Cited by 7,750
Blei, D. M. (2012) · Communications of the ACM · doi:10.1145/2133806.2133826 · Cited by 5,516
Culture, leadership, and organizations: the GLOBE study of 62 societies
(2005) · Choice Reviews Online · doi:10.5860/choice.42-4132 · Cited by 5,058
Harris, Z. S. (1954) · WORD · doi:10.1080/00437956.1954.11659520 · Cited by 4,807
Journal of Statistical Software
de Leeuw, J. (2009) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.10 · Cited by 3,651
Quantitative Analysis of Culture Using Millions of Digitized Books
Michel, J.-B., Shen, Y. K., Aiden, A. P., Veres, A., Gray, M. K., The Google Books Team, Pickett, J. P., Hoiberg, D., Clancy, D., Norvig, P., et al. (2010) · Science · doi:10.1126/science.1199644 · Cited by 3,235
Research works printed but not linked: 6
- Berente N., 2014, Paper presented at the 20th Americas Conference on Information Systems (AMCIS)
- Blei D., 2003, Journal of Machine Learning Research, 3, 993
- Frawley W., 1992, Al Magazine, 13, 57
- Jagarlamudi J., 2012, Paper presented at the 13th Conference of the European Chapter of the Association for Computational Linguistics
- Mimno D., 2011, Paper presented at the Conference on empirical methods in natural language processing
- Nguyen L., 2015, Paper presented at the Pacific-Asia Knowledge Discovery and Data Mining
Cited by
Sorted by citations
Marzi, G., Balzano, M., Caputo, A., & Pellegrini, M. M. (2024) · International Journal of Management Reviews · doi:10.1111/ijmr.12381 · Cited by 831
Goh, K. H., Wang, L., Yeow, A. Y. K., Poh, H., Li, K., Yeow, J. J. L., & Tan, G. Y. H. (2021) · Nature Communications · doi:10.1038/s41467-021-20910-4 · Cited by 415
Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations
Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2020) · Organizational Research Methods · doi:10.1177/1094428120971683 · Cited by 445
Artificial intelligence and the conduct of literature reviews
Wagner, G., Lukyanenko, R., & Paré, G. (2021) · Journal of Information Technology · doi:10.1177/02683962211048201 · Cited by 364
Hacker, J. V., Brocke, J. V., Handali, J. P., Otto, M., & Schneider, J. (2020) · European Journal of Information Systems · doi:10.1080/0960085x.2020.1814680 · Cited by 315
Metadata
- Authors
- Schmiedel, T., Müller, O., & vom Brocke, J.
- Affiliations
- University of Liechtenstein (LI)
- IT University of Copenhagen (DK)
- University of Liechtenstein, Liechtenstein
- Corresponding author
- Schmiedel, Theresa
- ORCID
- Schmiedel, Theresa
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2018-05-06
- Volume
- 22
- Issue
- 4
- Pages
- 941-968
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2801182247
- Cited by
- 319
- References
- 51
- Citations by year
- 2026: 34 · 2025: 54 · 2024: 53 · 2023: 61 · 2022: 44 · 2021: 42 · 2020: 23 · 2019: 6 · 2018: 2
- FWCI
- 67.52
- Type
- journal article
- Language
- en
- Open access
- green
- pure.itu.dk
- Locations
- Organizational Research Methods (publishedVersion)
- IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion, other-oa)
- Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- topic modeling, structural topic modeling, text mining, organizational culture, employee perceptions, Glassdoor reviews, Fortune 500 companies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
