Gable J. S. M., Sauvayre R., Chauvière C. (2023), « Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study », Journal of Medical Internet Research. Vol. 25.
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 type of arguments used by the Twitter users. This study shows that the debate about mandatory vaccination and immunity passports mostly used “con” arguments (47%) and “scientific” arguments (39%). Moreover, a political decision based on scientific arguments leads citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination.
Keywords: mandatory vaccination; public policy; public health measures; COVID-19; vaccine; social media analysis; Twitter; natural language processing, deep learning.
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 type of arguments used by the Twitter users. This study shows that the debate about mandatory vaccination and immunity passports mostly used “con” arguments (47%) and “scientific” arguments (39%). Moreover, a political decision based on scientific arguments leads citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination.
Keywords: mandatory vaccination; public policy; public health measures; COVID-19; vaccine; social media analysis; Twitter; natural language processing, deep learning.
