Misinformation about the COVID-19 Vaccine in Online Catholic Media

Author:

Israel-Turim Verónica1ORCID,Laferrara Valentina1,Rego Ana Regina2ORCID,Micó-Sanz Josep Lluís1

Affiliation:

1. Blanquerna School of Communications and International Relations, Ramon Llull University, 08022 Barcelona, Spain

2. Rede Nacional de Combate à Desinformação RNCd, Rio de Janeiro 21941-853, Brazil

Abstract

During the COVID-19 pandemic, online media were the most widely used sources of scientific information. Often, they are also the only ones on science-related topics. Research has shown that much of the information available on the Internet about the health crisis lacked scientific rigor, and that misinformation about health issues can pose a threat to public health. In turn, millions of Catholics were found to be demonstrating against vaccination against COVID-19 based on “false” and misleading religious arguments. This research analyses publications about the vaccine in Catholic online media with the aim of understanding the presence of information (and misinformation) in this community. An algorithm designed for each media outlet collected COVID-19 vaccine-related publications from 109 Catholic media outlets in five languages. In total, 970 publications were analysed for journalistic genres, types of headlines and sources of information. The results show that most publications are informative and most of their headlines are neutral. However, opinion articles have mostly negative headlines. Furthermore, a higher percentage of the opinion authors come from the religious sphere and most of the sources cited are religious. Finally, 35% of the publications relate the vaccine to the framing issue of abortion.

Funder

Google News Initiative

Publisher

MDPI AG

Subject

Pharmacology (medical),Infectious Diseases,Drug Discovery,Pharmacology,Immunology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Factors Influencing the Healthcare Workers’ Willingness to Receive the COVID-19 Booster Dose in Tuscany (Italy);Vaccines;2023-11-24

2. COVID-19 Misinformation Detection on Weibo by Support Vector Classifier;2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT);2023-10-13

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