Quantifying Changes in Vaccine Coverage in Mainstream Media as a Result of the COVID-19 Outbreak: Text Mining Study

Achieving herd immunity through vaccination depends upon the public's acceptance, which in turn relies on their understanding of its risks and benefits. The fundamental objective of public health messaging on vaccines is therefore the clear communication of often complex information and, increa...

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Vydané v:JMIR infodemiology Ročník 2; číslo 2; s. e35121
Hlavní autori: Christensen, Bente, Laydon, Daniel, Chelkowski, Tadeusz, Jemielniak, Dariusz, Vollmer, Michaela, Bhatt, Samir, Krawczyk, Konrad
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Canada JMIR Publications 01.07.2022
Predmet:
COVID-19 vaccines
Data mining
False information
Health care
Keywords
Language
Media coverage
Multimedia
News media
Original Paper
Pandemics
Severe acute respiratory syndrome coronavirus 2
Vaccine hesitancy
coverage
news
sentiment
data mining
change
hesitancy
media
COVID-19
vaccine
acceptance
outbreak
understanding
text mining
communication
social media
knowledge
ISSN:2564-1891, 2564-1891
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Shrnutí:Achieving herd immunity through vaccination depends upon the public's acceptance, which in turn relies on their understanding of its risks and benefits. The fundamental objective of public health messaging on vaccines is therefore the clear communication of often complex information and, increasingly, the countering of misinformation. The primary outlet shaping public understanding is mainstream online news media, where coverage of COVID-19 vaccines was widespread. We used text-mining analysis on the front pages of mainstream online news to quantify the volume and sentiment polarization of vaccine coverage. We analyzed 28 million articles from 172 major news sources across 11 countries between July 2015 and April 2021. We employed keyword-based frequency analysis to estimate the proportion of overall articles devoted to vaccines. We performed topic detection using BERTopic and named entity recognition to identify the leading subjects and actors mentioned in the context of vaccines. We used the Vader Python module to perform sentiment polarization quantification of all collated English-language articles. The proportion of front-page articles mentioning vaccines increased from 0.1% to 4% with the outbreak of COVID-19. The number of negatively polarized articles increased from 6698 in 2015-2019 to 28,552 in 2020-2021. However, overall vaccine coverage before the COVID-19 pandemic was slightly negatively polarized (57% negative), whereas coverage during the pandemic was positively polarized (38% negative). Throughout the pandemic, vaccines have risen from a marginal to a widely discussed topic on the front pages of major news outlets. Mainstream online media has been positively polarized toward vaccines, compared with mainly negative prepandemic vaccine news. However, the pandemic was accompanied by an order-of-magnitude increase in vaccine news that, due to low prepandemic frequency, may contribute to a perceived negative sentiment. These results highlight important interactions between the volume of news and overall polarization. To the best of our knowledge, our work is the first systematic text mining study of front-page vaccine news headlines in the context of COVID-19.
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ISSN:2564-1891
2564-1891
DOI:10.2196/35121