Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48405, first published .
Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses

Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses

Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses

Maria A Parker   1 , MS, MPH, PhD ;   Danny Valdez   2 , PhD ;   Varun K Rao   1, 3 , MS ;   Katherine S Eddens   1 , MPH, PhD ;   Jon Agley   2 , MPH, PhD

1 Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States

2 Department of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States

3 Department of Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States

Corresponding Author:

  • Maria A Parker, MS, MPH, PhD
  • Department of Epidemiology and Biostatistics
  • School of Public Health
  • Indiana University Bloomington
  • 809 E. 9th St.
  • Bloomington, IN, 47405
  • United States
  • Phone: 1 812-856-5950
  • Email: map2@iu.edu