This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2208) Physician and Health Services Rating by Consumers (126) Machine Learning (1385) Natural Language Processing (644) Validity, Reliability, and Bias (89)

Published on in Vol 6, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34902, first published .
Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study

Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study

Understanding Gender Biases and Differences in Web-Based Reviews of Sanctioned Physicians Through a Machine Learning Approach: Mixed Methods Study

Authors of this article:

Julia Barnett1 Author Orcid Image ;   Margrét Vilborg Bjarnadóttir2 Author Orcid Image ;   David Anderson3 Author Orcid Image ;   Chong Chen2 Author Orcid Image
Article Authors Cited by (1) Tweetations (9) Metrics

Julia Barnett   1 , BBA, MS ;   Margrét Vilborg Bjarnadóttir   2 , BSc, PhD ;   David Anderson   3 , BS, PhD ;   Chong Chen   2 , BS, MS

1 Technology and Social Behavior, Northwestern University, Evanston, IL, United States

2 Robert H. Smith School of Business, University of Maryland, College Park, MD, United States

3 Villanova School of Business, Villanova University, Villanova, PA, United States

Corresponding Author:

  • Julia Barnett, BBA, MS
  • Technology and Social Behavior
  • Northwestern University
  • 2240 Campus Drive
  • Room 2-168 (Attention: Dept of Comm Studies)
  • Evanston, IL, 60208
  • United States
  • Phone: 1 847 491 7530
  • Email: JuliaBarnett@u.northwestern.edu