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

Yining HuaHang JiangShixu LinJie YangJoseph M PlasekDavid Westfall BatesLi Zhou

Published in: Journal of the American Medical Informatics Association : JAMIA (2022)

Our study found that social media users with have different perceptions and stances on off-label versus FDA-authorized drug use across different stages of COVID-19, indicating that health systems, regulatory agencies, and policymakers should design tailored strategies to monitor and reduce misinformation for promoting safe drug use. Our analysis pipeline and stance detection models are made public at https://github.com/ningkko/COVID-drug.

Keyphrases

social media
coronavirus disease
sars cov
healthcare
health information
primary care
mental health
respiratory syndrome coronavirus
transcription factor
machine learning
loop mediated isothermal amplification
sensitive detection