Using Twitter data to understand public perceptions of approved versus off-label use for COVID-19-related medications

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Yining Hua, Hang Jiang, Shixu Lin, Jie Yang, Joseph M. Plasek, David W. Bates, Li Zhou

Published: 2022, Last Modified: 15 Oct 2025J. Am. Medical Informatics Assoc. 2022EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Understanding public discourse on emergency use of unproven therapeutics is essential to monitor safe use and combat misinformation. We developed a natural language processing-based pipeline to understand public perceptions of and stances on coronavirus disease 2019 (COVID-19)-related drugs on Twitter across time.