The DOI matches its Crossref record; 202 of the 202 references it cites were found in a registry or an index.
Topic Modeling in Management Research: Rendering New Theory from Textual Data
Open accessAbstract
Increasingly, management researchers are using topic modeling, a new method borrowed from computer science, to reveal phenomenon-based constructs and grounded conceptual relationships in textual data. By conceptualizing topic modeling as the process of rendering constructs and conceptual relationships from textual data, we demonstrate how this new method can advance management scholarship without turning topic modeling into a black box of complex computer-driven algorithms. We begin by comparing features of topic modeling to related techniques (content analysis, grounded theorizing, and natural language processing). We then walk through the steps of rendering with topic modeling and apply rendering to management articles that draw on topic modeling. Doing so enables us to identify and discuss how topic modeling has advanced management theory in five areas: detecting novelty and emergence, developing inductive classification systems, understanding online audiences and products, analyzing frames and social movements, and understanding cultural dynamics. We conclude with a review of new topic modeling trends and revisit the role of researcher interpretation in a world of computer-driven textual analysis.
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Capturing causal complexity: Heuristics for configurational theorizing
Furnari, S., Crilly, D., Misangyi, V. F., Greckhamer, T., Fiss, P. C., & Aguilera, R. V. (2021) · Academy of Management Review · doi:10.5465/amr.2019.0298 · Cited by 861
Chen, X., Zou, D., Cheng, G., & Xie, H. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103855 · Cited by 403
Theory building with big data-driven research–Moving away from the “What” towards the “Why”
Kar, A. K., & Dwivedi, Y. K. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102205 · Cited by 301
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Metadata
- Authors
- Hannigan, T. R., Haans, R. F. J., Vakili, K., Tchalian, H., Glaser, V. L., Wang, M. S., Kaplan, S., & Jennings, P. D.
- Venue
- Academy of Management Annals
- Publisher
- Academy of Management
- Published
- 2019-07
- Volume
- 13
- Issue
- 2
- Pages
- 586-632
- ISSN
- 1941-6067 (ISSN-L)
- 1941-6520
- OpenAlex
- W2943121181
- Cited by
- 621
- References
- 202
- FWCI
- 157.24
- Type
- journal article
- Language
- en
- Open access
- green
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- Hannigan, T. R., Haans, R. F. J., Vakili, K., Tchalian, H., Glaser, V. L., Wang, M. S., Kaplan, S., & Jennings, P. D. (2019). Topic Modeling in Management Research: Rendering New Theory from Textual Data. Academy of Management Annals. https://doi.org/10.5465/annals.2017.0099
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
