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

    33 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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