Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58919, first published .
Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Public Response to Federal Electronic Cigarette Regulations Analyzed Using Social Media Data Through Natural Language Processing: Topic Modeling Study

Shuo-Yu Lin   1 , PhD ;   Sahithi Kiran Tulabandu   2 , MS, PharmD ;   J Randy Koch   3 , PhD ;   Rashelle Hayes   4 , PhD ;   Andrew Barnes   5 , PhD ;   Hemant Purohit   6 , PhD ;   Songqing Chen   7 , PhD ;   Bo Han   7 , PhD ;   Hong Xue   1 , PhD

1 Department of Health Administration and Policy, George Mason University, Fairfax, VA, United States

2 WVU Health Affairs Institute, Morgantown, WV, United States

3 Department of Psychology, Virginia Commonwealth University, Richmond, VA, United States

4 Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States

5 Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA, United States

6 Department of Information Sciences and Technology, George Mason University, Fairfax, VA, United States

7 Department of Computer Science, George Mason University, Fairfax, VA, United States

Corresponding Author:

  • Hong Xue, PhD
  • Department of Health Administration and Policy
  • George Mason University
  • 4400 University Dr
  • Fairfax, VA, 22030
  • United States
  • Phone: 1 703-993-9833
  • Email: hxue4@gmu.edu