Actions Speak Louder Than Words : Sentiment and Topic Analysis of COVID-19 Vaccination on Twitter and Vaccine Uptake

Journal article


Yousef, Murooj, Dietrich, Timo and Rundle-Thiele, Sharyn. (2022). Actions Speak Louder Than Words : Sentiment and Topic Analysis of COVID-19 Vaccination on Twitter and Vaccine Uptake. JMIR Formative Research. 6(9), pp. 1-23. https://doi.org/10.2196/37775
AuthorsYousef, Murooj, Dietrich, Timo and Rundle-Thiele, Sharyn
Abstract

Background: The lack of trust in vaccines is a major contributor to vaccine hesitancy. To overcome vaccine hesitancy for the COVID-19 vaccine, the Australian government launched multiple public health campaigns to encourage vaccine uptake. This sentiment analysis examines the effect of public health campaigns and COVID-19–related events on sentiment and vaccine uptake.

Objective: This study aims to examine the relationship between sentiment and COVID-19 vaccine uptake and government actions that impacted public sentiment about the vaccine.

Methods: Using machine learning methods, we collected 137,523 publicly available English language tweets published in Australia between February and October 2021 that contained COVID-19 vaccine–related keywords. Machine learning methods were used to extract topics and sentiments relating to COVID-19 vaccination. The relationship between public vaccination sentiment on Twitter and vaccine uptake was examined.

Results: The majority of collected tweets expressed negative (n=91,052, 66%) rather than positive (n=21,686, 16%) or neutral (n=24,785, 18%) sentiments. Topics discussed within the study time frame included the role of the government in the vaccination rollout, availability and accessibility of the vaccine, and vaccine efficacy. There was a significant positive correlation between negative sentiment and the number of vaccine doses administered daily (r267=.15, P<.05), with positive sentiment showing the inverse effect. Public health campaigns, lockdowns, and antivaccination protests were associated with increased negative sentiment, while vaccination mandates had no significant effect on sentiment.

Conclusions: The study findings demonstrate that negative sentiment was more prevalent on Twitter during the Australian vaccination rollout but vaccine uptake remained high. Australians expressed anger at the slow rollout and limited availability of the vaccine during the study period. Public health campaigns, lockdowns, and antivaccination rallies increased negative sentiment. In contrast, news of increased vaccine availability for the public and government acquisition of more doses were key government actions that reduced negative sentiment. These findings can be used to inform government communication planning.

KeywordsCOVID-19 ; COVID-19 vaccination; sentiment analysis; public health campaigns ; vaccine uptake; Twitter; social media; vaccines
Year01 Jan 2022
JournalJMIR Formative Research
Journal citation6 (9), pp. 1-23
PublisherJMIR Publications Inc.
ISSN2561-326X
Digital Object Identifier (DOI)https://doi.org/10.2196/37775
Web address (URL)https://formative.jmir.org/2022/9/e37775
Open accessPublished as ‘gold’ (paid) open access
Research or scholarlyResearch
Page range1-23
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Print15 Sep 2022
Publication process dates
Accepted23 Aug 2022
Deposited13 Jun 2024
Additional information

© Murooj Yousef, Timo Dietrich, Sharyn Rundle-Thiele.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

Preprint version:
https://preprints.jmir.org/preprint/37775?__hstc=102212634.0e90f71dc...

Place of publicationCanada
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