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The Prevalence of mRNA Related Discussions during the Post-COVID-19 Era

Kokkinakis, Dimitrios ; Bruinsma, Bastiaan and Hammarlin, Mia Marie LU orcid (2023) 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 In Studies in Health Technology and Informatics 302. p.798-802
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
event detection, mRNA vaccines, natural language processing, structural topic modeling, Swedish internet forum, Swedish tweets, vaccine hesitancy
host publication
Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023
series title
Studies in Health Technology and Informatics
editor
Hagglund, Maria ; Blusi, Madeleine ; Bonacina, Stefano ; Nilsson, Lina ; Madsen, Inge Cort ; Pelayo, Sylvia ; Moen, Anne ; Benis, Arriel ; Lindskold, Lars and Gallos, Parisis
volume
302
pages
5 pages
publisher
IOS Press
conference name
33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023
conference location
Gothenburg, Sweden
conference dates
2023-05-22 - 2023-05-25
external identifiers
  • pmid:37203498
  • scopus:85159764697
ISSN
1879-8365
0926-9630
ISBN
9781643683881
DOI
10.3233/SHTI230269
language
English
LU publication?
yes
id
170ddbb1-5a63-44a1-8a6b-2346ecf18d40
date added to LUP
2023-08-21 12:41:18
date last changed
2024-04-20 01:06:09
@inproceedings{170ddbb1-5a63-44a1-8a6b-2346ecf18d40,
  abstract     = {{<p>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.</p>}},
  author       = {{Kokkinakis, Dimitrios and Bruinsma, Bastiaan and Hammarlin, Mia Marie}},
  booktitle    = {{Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023}},
  editor       = {{Hagglund, Maria and Blusi, Madeleine and Bonacina, Stefano and Nilsson, Lina and Madsen, Inge Cort and Pelayo, Sylvia and Moen, Anne and Benis, Arriel and Lindskold, Lars and Gallos, Parisis}},
  isbn         = {{9781643683881}},
  issn         = {{1879-8365}},
  keywords     = {{event detection; mRNA vaccines; natural language processing; structural topic modeling; Swedish internet forum; Swedish tweets; vaccine hesitancy}},
  language     = {{eng}},
  pages        = {{798--802}},
  publisher    = {{IOS Press}},
  series       = {{Studies in Health Technology and Informatics}},
  title        = {{The Prevalence of mRNA Related Discussions during the Post-COVID-19 Era}},
  url          = {{http://dx.doi.org/10.3233/SHTI230269}},
  doi          = {{10.3233/SHTI230269}},
  volume       = {{302}},
  year         = {{2023}},
}