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

JMIR Theme Issue 2020/21: COVID-19 Special Issue (850) Drug Repurposing and Off-Label Use (9) Infodemiology and Infoveillance (516) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (806) Infectious Diseases (non-STD/STI) (541) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (405) Mass Media/Social Media Communication and Campaigns (174) Outbreak and Pandemic Preparedness and Management (632) Theme Issue 2020-2021: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (633)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20044, first published .
Impact of Trump's Promotion of Unproven COVID-19 Treatments and Subsequent Internet Trends: Observational Study

Impact of Trump's Promotion of Unproven COVID-19 Treatments and Subsequent Internet Trends: Observational Study

Impact of Trump's Promotion of Unproven COVID-19 Treatments and Subsequent Internet Trends: Observational Study

Authors of this article:

Kacper Niburski 1 Author Orcid Image ;   Oskar Niburski 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (16) Metrics

Journals

  1. Parrish D. From the Editor—Reflecting on 2020: Science, Values, and Politics. Journal of Social Work Education 2021;57(1):1 View
  2. Mackey T, Purushothaman V, Haupt M, Nali M, Li J. Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter. The Lancet Digital Health 2021;3(2):e72 View
  3. Haupt M, Li J, Mackey T. Identifying and characterizing scientific authority-related misinformation discourse about hydroxychloroquine on twitter using unsupervised machine learning. Big Data & Society 2021;8(1):205395172110138 View