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

Infodemiology and Infoveillance (1369) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1666) New Methods (964) Natural Language Processing (708) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050)

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

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

Authors of this article:

Heather Cole-Lewis1 Author Orcid Image ;   Arun Varghese1 Author Orcid Image ;   Amy Sanders1 Author Orcid Image ;   Mary Schwarz1 Author Orcid Image ;   Jillian Pugatch1 Author Orcid Image ;   Erik Augustson2 Author Orcid Image
Article Authors Cited by (53) Tweetations (47) Metrics

Heather Cole-Lewis   1 , PhD, MPH,MA ;   Arun Varghese   1 , MEng, MPA ;   Amy Sanders   1 , MA ;   Mary Schwarz   1 ;   Jillian Pugatch   1 , MPH ;   Erik Augustson   2 , PhD,MPH

1 ICF International, Rockville, MD, United States

2 National Cancer Institute, Tobacco Control Research Branch, Bethesda, MD, United States

Corresponding Author:

  • Erik Augustson, PhD,MPH
  • National Cancer Institute
  • Tobacco Control Research Branch
  • 9609 Medical Center Drive
  • MSC 9761
  • Bethesda, MD, 20892
  • United States
  • Phone: 1 240-276-6774
  • Fax: 1 240-276-7907
  • Email: augustse@mail.nih.gov