Evidence map›Paper›PMID 36007136›Full record

ArticleJMIR formative research2022

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

Murooj Yousef, Timo Dietrich, Sharyn Rundle-Thiele

Abstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Murooj Yousef *Social Marketing @ Griffith, Department of Marketing, Griffith University, Nathan, Australia.ORCID https://orcid.org/0000-0002-8215-2627
Timo Dietrich *Social Marketing @ Griffith, Department of Marketing, Griffith University, Nathan, Australia.ORCID https://orcid.org/0000-0003-4824-6117
Sharyn Rundle-Thiele *Social Marketing @ Griffith, Department of Marketing, Griffith University, Nathan, Australia.ORCID https://orcid.org/0000-0003-2536-3767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

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

methodsUsing 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.

resultsThe 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 (r

conclusionsThe 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.

Indexed as

COVID-19COVID-19 vaccinationpublic health campaignssentiment analysissocial mediaTwittervaccinesvaccine uptake

Identifiers

PMID36007136
PMCPMC9484485

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.