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

ABSTRACT:

Objective

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.

Methods

This retrospective study included 609 189 US-based tweets between January 29, 2020 and November 30, 2021 on 4 drugs that gained wide public attention during the COVID-19 pandemic: (1) Hydroxychloroquine and Ivermectin, drug therapies with anecdotal evidence; and (2) Molnupiravir and Remdesivir, FDA-approved treatment options for eligible patients. Time-trend analysis was used to understand the popularity and related events. Content and demographic

SUBMITTER: Hua Y 

PROVIDER: S-EPMC9278189 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature