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

New Methods (964) Peer-to-Peer Support and Online Communities (652) Natural Language Processing (708)

Published on in Vol 17, No 8 (2015): August

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text

Authors of this article:

Albert Park1 Author Orcid Image ;   Andrea L Hartzler2 Author Orcid Image ;   Jina Huh3 Author Orcid Image ;   David W McDonald4 Author Orcid Image ;   Wanda Pratt5 Author Orcid Image
Article Authors Cited by (29) Tweetations (25) Metrics

Albert Park   1 , PhD ;   Andrea L Hartzler   2 , PhD ;   Jina Huh   3 , PhD ;   David W McDonald   4 , PhD ;   Wanda Pratt   5 , PhD

1 Department of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, WA, United States

2 Group Health Research Institute, Seattle, WA, United States

3 Department of Biomedical Informatics, University of California San Diego, San Diego, CA, United States

4 Human Centered Design & Engineering, University of Washington, Seattle, WA, United States

5 The Information School, University of Washington, Seattle, WA, United States

Corresponding Author:

  • Albert Park, PhD
  • Department of Biomedical Informatics and Medical Education
  • School of Medicine
  • University of Washington
  • Box SLU-BIME 358047, 850 Republican St, Building C
  • Seattle, WA, 98109-4714
  • United States
  • Phone: 1 206-743-7843
  • Fax: 1 206-616-3152
  • Email: alpark1216@gmail.com