Previously submitted to: Journal of Medical Internet Research (no longer under consideration since May 07, 2024)
Date Submitted: Oct 26, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Sentiment analysis of vaccine-related online newspaper comments increased after the emergence of COVID-19: Exploratory Analysis
ABSTRACT
Background:
Examining longitudinal public opinion around the first COVID-19 vaccine in 2020 provides historical context and a baseline for examining how future vaccines are received. Online comments from news articles provide one source of data for measuring such public opinion.
Objective:
The goal of this short communication uses online comments scraped from The New York Times to measure the sentiment of both the overall comments and vaccine-related comments for the years 2017-2020.
Methods:
We measured sentiment analysis of comments from 2017-2020. We applied the VADER model (Valence Aware Dictionary and sEntiment Reasoner).
Results:
The sentiment for vaccine-related comments increased after March of 2020 and continued through December 2020.
Conclusions:
This analysis provides researchers with a baseline of comparison for future social media discussions to better understand the reception of vaccines.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.