Natural language processing (NLP) in management research: A literature review

Yue Kang, Zhao Cai, Chee Wee Tan, Qian Huang, Hefu Liu

Research output: Journal PublicationReview articlepeer-review

48 Citations (Scopus)

Abstract

Natural language processing (NLP) is gaining momentum in management research for its ability to automatically analyze and comprehend human language. Yet, despite its extensive application in management research, there is neither a comprehensive review of extant literature on such applications, nor is there a detailed walkthrough on how it can be employed as an analytical technique. To this end, we review articles in the UT Dallas List of 24 Leading Business Journals that employ NLP as their focal analytical technique to elucidate how textual data can be harnessed for advancing management theories across multiple disciplines. We describe the available toolkits and procedural steps for employing NLP as an analytical technique as well as its advantages and disadvantages. In so doing, we highlight the managerial and technological challenges associated with the application of NLP in management research in order to guide future inquires.

Original languageEnglish
Pages (from-to)139-172
Number of pages34
JournalJournal of Management Analytics
Volume7
Issue number2
DOIs
Publication statusPublished - 2 Apr 2020

Keywords

  • literature review
  • machine learning
  • natural language processing
  • sentiment analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Business, Management and Accounting (miscellaneous)
  • Statistics, Probability and Uncertainty

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