The Prevalence of mRNA Related Discussions During the Post-COVID-19 Era
Artikel i vetenskaplig tidskrift, 2023

Vaccinations are one of the most significant interventions to public health, but vaccine hesitancy and skepticism are raising serious concerns for a portion of the population in many countries, including Sweden. In this study, we use Swedish social media data and structural topic modeling to automatically identify mRNA-vaccine related discussion themes and gain deeper insights into how people's refusal or acceptance of the mRNA technology affects vaccine uptake. Our point of departure is a scientific study published in February 2022, which seems to once again sparked further suspicion and concern and highlight the necessity to focus on issues about the nature and trustworthiness in vaccine safety. Structural topic modelling is a statistical method that facilitates the study of topic prevalence, temporal topic evolution, and topic correlation automatically. Using such a method, our research goal is to identify the current understanding of the mechanisms on how the public perceives the mRNA vaccine in the light of new experimental findings.

Swedish internet forum

event detection

Swedish tweets

natural language processing

structural topic modeling

vaccine hesitancy

mRNA vaccines

Författare

Dimitrios Kokkinakis

Göteborgs universitet

Sebastianus Cornelis Jacobus Bruinsma

Chalmers, Data- och informationsteknik, Data Science och AI

Mia Marie Hammarlin

Lunds universitet

Studies in health technology and informatics

09269630 (ISSN) 18798365 (eISSN)

Vol. 302 798-802

Ämneskategorier

Språkteknologi (språkvetenskaplig databehandling)

DOI

10.3233/SHTI230269

PubMed

37203498

Mer information

Senast uppdaterat

2023-06-09