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

Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Mass Media/Social Media Communication and Campaigns (461)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18401, first published .
Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach

Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach

Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach

Authors of this article:

Jane M Zhu1 Author Orcid Image ;   Abeed Sarker2 Author Orcid Image ;   Sarah Gollust3 Author Orcid Image ;   Raina Merchant4 Author Orcid Image ;   David Grande5 Author Orcid Image
Article Authors Cited by (3) Tweetations (14) Metrics

Journals

  1. Chandrasekaran R, Mehta V, Valkunde T, Moustakas E. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e22624 View
  2. Yang Y, Al-Garadi M, Bremer W, Zhu J, Grande D, Sarker A. Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid. Journal of Medical Internet Research 2021;23(5):e26616 View
  3. Weber M, Armour V, Lindstadt C, Yanovitzky I. Testing Multiple Methods to Effectively Promote Use of a Knowledge Portal to Health Policy Makers: Quasi-Experimental Evaluation. Journal of Medical Internet Research 2023;25:e41997 View