Making Words Count: Computational Linguistics in Management Research

Authors

• Joseph J. Simpson, The University of Texas Rio Grande ValleyFollow
• Richard A. Hunt, Virginia Polytechnic Institute and State University
• David M. Townsend, Virginia Polytechnic Institute and State University
• Judy Rady, University of Kansas
• Elham Asgari, Michigan Technological University
• Mohammad Rady, Virginia Polytechnic Institute and State University
• Daniel J. Beal, Virginia Polytechnic Institute and State University

Document Type

Article

Publication Date

1-1-2026

Abstract

In recent years, a rapidly growing number of management scholars are using computational linguistics (CL) to analyze vast corpora of naturally occurring organizational language. Yet the rapid adoption of CL methods has outpaced the development of shared standards for linking theoretical constructs, linguistic data, and computational measurement. We synthesize 353 articles published in leading management journals for 2013–2025, identifying four recurring challenges shaping the credibility of CL-based research: misalignment between constructs and textual corpora, unnecessary model complexity, the opacity of large language model workflows, and insufficient transparency in reporting. Building on these patterns, we develop four integrative design principles—construct-language fit, minimal sufficient complexity, LLM sensitivity and auditability, and disclosure-as-assessability—and identify key research implications that reposition CL as a theoretically consequential lens for management scholarship.

Comments

© The Author(s) 2026. Under CC-BY

Recommended Citation

Simpson, J.J., Hunt, R.A., Townsend, D.M., Rady, J., Asgari, E., Rady, M. and Beal, D.J., 2026. Making Words Count: Computational Linguistics in Management Research. Journal of Management, p.01492063261465289. https://doi.org/10.1177/01492063261465289

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Publication Title

Journal of Management

DOI

10.1177/01492063261465289