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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 29, 2023
Date Accepted: Oct 18, 2023
Date Submitted to PubMed: Oct 18, 2023

The final, peer-reviewed published version of this preprint can be found here:

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

Gable JSM, Sauvayre R, Chauvière C

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

J Med Internet Res 2023;25:e49435

DOI: 10.2196/49435

PMID: 37850906

PMCID: 10669926

Fight against the mandatory Covid-19 immunity passport on Twitter: a natural language processing study

  • Jessica S. M. Gable; 
  • Romy Sauvayre; 
  • Cédric Chauvière

ABSTRACT

To contain and curb the spread of COVID-19, the governments of countries around the world have used different strategies (lockdown, mandatory vaccination, immunity passports, voluntary social distancing, etc.). This article aims to examine the effects of the public announcement of a binding political decision presented by the president of the French Republic, Emmanuel Macron, on July 12, 2021, which imposed vaccination on caregivers and an immunity passport on all French people to access restaurants, cinemas, bars, etc. To measure the effects of these announcements, 901,908 unique tweets posted on Twitter between July 12, 2021, and August 11, 2021, were extracted. A neural network was constructed to examine the arguments of the tweets and to identify the types of arguments employed by the Twitter users. This study shows that in the debate about mandatory vaccination and immunity passports, mostly “con” arguments (47%) and “scientific” arguments (39%) were used. Moreover, a political decision based on scientific arguments led citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination.


 Citation

Please cite as:

Gable JSM, Sauvayre R, Chauvière C

Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study

J Med Internet Res 2023;25:e49435

DOI: 10.2196/49435

PMID: 37850906

PMCID: 10669926

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