Perceived experts are prevalent and influential within an antivaccine community on Twitter.
PNAS Nexus
; 3(2): pgae007, 2024 Feb.
Article
em En
| MEDLINE
| ID: mdl-38328781
ABSTRACT
Perceived experts (i.e. medical professionals and biomedical scientists) are trusted sources of medical information who are especially effective at encouraging vaccine uptake. The role of perceived experts acting as potential antivaccine influencers has not been characterized systematically. We describe the prevalence and importance of antivaccine perceived experts by constructing a coengagement network of 7,720 accounts based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the antivaccine community. Perceived experts had a sizable presence across the coengagement network, including within the antivaccine community where they were 9.8% of individual, English-language users. Perceived experts within the antivaccine community shared low-quality (misinformation) sources at similar rates and academic sources at higher rates compared to perceived nonexperts in that community. Perceived experts occupied important network positions as central antivaccine users and bridges between the antivaccine and provaccine communities. Using propensity score matching, we found that perceived expertise brought an influence boost, as perceived experts were significantly more likely to receive likes and retweets in both the antivaccine and provaccine communities. There was no significant difference in the magnitude of the influence boost for perceived experts between the two communities. Social media platforms, scientific communications, and biomedical organizations may focus on more systemic interventions to reduce the impact of perceived experts in spreading antivaccine misinformation.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Risk_factors_studies
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article