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

Public (e)Health, Digital Epidemiology and Public Health Informatics (646) Natural Language Processing (650) Information Models (22) Machine Learning (1401) Smoking Cessation (521)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30257, first published .
Identifying Electronic Nicotine Delivery System Brands and Flavors on Instagram: Natural Language Processing Analysis

Identifying Electronic Nicotine Delivery System Brands and Flavors on Instagram: Natural Language Processing Analysis

Identifying Electronic Nicotine Delivery System Brands and Flavors on Instagram: Natural Language Processing Analysis

Authors of this article:

Rob Chew1 Author Orcid Image ;   Michael Wenger1 Author Orcid Image ;   Jamie Guillory2 Author Orcid Image ;   James Nonnemaker2 Author Orcid Image ;   Annice Kim2 Author Orcid Image
Article Authors Cited by (4) Tweetations (9) Metrics

Rob Chew   1 , MSc ;   Michael Wenger   1 , BSc ;   Jamie Guillory   2 , PhD ;   James Nonnemaker   2 , PhD ;   Annice Kim   2 , PhD

1 Center for Data Science, RTI International, Research Triangle Park, NC, United States

2 Center for Health Analytics, Media, and Policy, RTI International, Research Triangle Park, NC, United States

Corresponding Author:

  • Rob Chew, MSc
  • Center for Data Science
  • RTI International
  • 3040 East Cornwallis Road
  • Research Triangle Park, NC, 27709
  • United States
  • Phone: 1 919 541 5823
  • Email: rchew@rti.org