Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms.

Journal: Journal of medical Internet research
Published Date: Nov 12, 2018

Abstract

BACKGROUND: An increasing number of doctor reviews are being generated by patients on the internet. These reviews address a diverse set of topics (features), including wait time, office staff, doctor's skills, and bedside manners. Most previous work on automatic analysis of Web-based customer reviews assumes that (1) product features are described unambiguously by a small number of keywords, for example, battery for phones and (2) the opinion for each feature has a positive or negative sentiment. However, in the domain of doctor reviews, this setting is too restrictive: a feature such as visit duration for doctor reviews may be expressed in many ways and does not necessarily have a positive or negative sentiment.

Authors

  • Ryan Rivas
    Department of Computer Science and Engineering, University of California, Riverside, Riverside, CA, United States.
  • Niloofar Montazeri
    Department of Computer Science and Engineering, University of California, Riverside, Riverside, CA, United States.
  • Nhat Xt Le
    Department of Computer Science and Engineering, University of California, Riverside, Riverside, CA, United States.
  • Vagelis Hristidis
    Department of Computer Science and Engineering, University of California, Riverside, Riverside, CA, United States.

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