Augmenting Qualitative Text Analysis with Natural Language Processing: Methodological Study.

Journal: Journal of medical Internet research
Published Date: Jun 29, 2018

Abstract

BACKGROUND: Qualitative research methods are increasingly being used across disciplines because of their ability to help investigators understand the perspectives of participants in their own words. However, qualitative analysis is a laborious and resource-intensive process. To achieve depth, researchers are limited to smaller sample sizes when analyzing text data. One potential method to address this concern is natural language processing (NLP). Qualitative text analysis involves researchers reading data, assigning code labels, and iteratively developing findings; NLP has the potential to automate part of this process. Unfortunately, little methodological research has been done to compare automatic coding using NLP techniques and qualitative coding, which is critical to establish the viability of NLP as a useful, rigorous analysis procedure.

Authors

  • Timothy C Guetterman
    Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Tammy Chang
    Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Melissa DeJonckheere
    Department of Family Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Tanmay Basu
    Ramakrishna Mission Vivekananda Educational and Research Institute, Belur Math, West Bengal, India.
  • Elizabeth Scruggs
    Department of Internal Medicine-Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • V G Vinod Vydiswaran
    Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, USA.

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