Abstract

This article demonstrates the value of sentiment analysis for contextualizing audiences in Rhetoric of Health and Medicine (RHM) by comparing vaccine related newspaper comments to non-vaccine related comments in the New York Times from 2017–2023 (n = 22,330,999). Our results show that while all comments skew negative, following a similar trend line, after the emergence of COVID-19, vaccine related comments decouple from the negative trend of baseline non-vaccine comments, becoming more negative and volatile. These results raise additional questions about the nature of the negativity for vaccine related comments, and we provide a properly sampled dataset for follow-up research to encourage iterative investigation into the public response to vaccine policy. In addition to these findings, this article calls for broader engagement with Natural Language Processing (NLP) and data science in RHM.