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Background: 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).

Objective: This study aims to examine the reactions produced by 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, and so forth.

Methods: To measure these announcement reactions, 901,908 unique tweets posted on Twitter (Twitter Inc) between July 12 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 used by Twitter users.

Results: This study shows that in the debate about mandatory vaccination and immunity passports, mostly "con" arguments (399,803/847,725, 47%; χ 2 6 =952.8; P<.001) and "scientific" arguments (317,156/803,583, 39%; χ 2 6 =5006.8; P<.001) were used.

Conclusions: This study shows that during July and August 2021, social events permeating the public sphere and discussions about mandatory vaccination and immunity passports collided on Twitter. Moreover, a political decision based on scientific arguments led citizens to challenge it using pseudoscientific arguments contesting the effectiveness of vaccination and the validity of these political decisions.

(©Jessica S M Gable, Romy Sauvayre, Cédric Chauvière. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.11.2023.)

Titel:	Fight Against the Mandatory COVID-19 Immunity Passport on Twitter: Natural Language Processing Study.
Autor/in / Beteiligte Person:	Gable, JSM ; Sauvayre, R ; Chauvière, C
Link:	Full Text Finder (Volltext)
Zeitschrift:	Journal of medical Internet research, Jg. 25 (2023-11-23), S. e49435
Veröffentlichung:	<2011- > : Toronto : JMIR Publications ; <i>Original Publication</i>: [Pittsburgh, PA? : s.n., 1999-, 2023
Medientyp:	academicJournal
ISSN:	1438-8871 (electronic)
DOI:	10.2196/49435
Schlagwort:	Humans Natural Language Processing Communicable Disease Control Neural Networks, Computer COVID-19 prevention & control Social Media
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [J Med Internet Res] 2023 Nov 23; Vol. 25, pp. e49435. <i>Date of Electronic Publication: </i>2023 Nov 23. MeSH Terms: COVID-19* / prevention & control ; Social Media* ; Humans ; Natural Language Processing ; Communicable Disease Control ; Neural Networks, Computer References: Int J Environ Res Public Health. 2021 Dec 09;18(24):. (PMID: 34948592) ; Vaccines (Basel). 2022 May 15;10(5):. (PMID: 35632537) ; Vaccines (Basel). 2022 Mar 13;10(3):. (PMID: 35335070) ; Healthcare (Basel). 2022 Feb 08;10(2):. (PMID: 35206935) ; Front Public Health. 2022 Feb 04;9:801176. (PMID: 35186875) ; Hum Vaccin Immunother. 2022 Nov 30;18(5):2073757. (PMID: 35612817) ; Lancet. 2020 May 23;395(10237):1595-1598. (PMID: 32380041) ; Lancet. 2020 Feb 29;395(10225):676. (PMID: 32113495) ; Vaccines (Basel). 2022 Nov 15;10(11):. (PMID: 36423024) ; Risk Manag Healthc Policy. 2022 Apr 14;15:643-655. (PMID: 35444478) ; Vaccine. 2021 Sep 15;39(39):5499-5505. (PMID: 34452774) ; Nat Med. 2022 Feb;28(2):232-235. (PMID: 35022575) ; Proc Assoc Inf Sci Technol. 2020;57(1):e252. (PMID: 33173813) ; Vaccines (Basel). 2022 Jan 08;10(1):. (PMID: 35062751) ; J Med Internet Res. 2022 Jan 6;24(1):e32329. (PMID: 34870605) ; J Bioeth Inq. 2022 Sep;19(3):451-465. (PMID: 35362931) ; Vaccines (Basel). 2022 Sep 02;10(9):. (PMID: 36146535) ; Vaccines (Basel). 2022 Mar 31;10(4):. (PMID: 35455292) ; Vaccine. 2022 Dec 5;40(51):7378-7388. (PMID: 35688728) ; Vaccine. 2022 Dec 5;40(51):7370-7377. (PMID: 35153092) ; Health Policy Technol. 2022 Jun;11(2):100635. (PMID: 35531440) ; MMWR Morb Mortal Wkly Rep. 2021 Aug 06;70(31):1059-1062. (PMID: 34351882) ; JDR Clin Trans Res. 2023 Apr;8(2):188-197. (PMID: 35191352) ; JMIR Med Inform. 2022 May 17;10(5):e37831. (PMID: 35512274) ; PLoS One. 2021 Nov 5;16(11):e0259362. (PMID: 34739509) ; JAMA. 2020 Jun 9;323(22):2241-2242. (PMID: 32374357) ; Front Psychiatry. 2021 Dec 07;12:774504. (PMID: 34950070) ; J Med Internet Res. 2023 Apr 24;25:e37237. (PMID: 36596215) ; Cureus. 2021 Aug 17;13(8):e17243. (PMID: 34540469) ; Vaccines (Basel). 2022 May 20;10(5):. (PMID: 35632568) ; BMJ Open. 2022 Jun 16;12(6):e060829. (PMID: 35710243) Contributed Indexing: Keywords: COVID-19; Twitter; deep learning; effectiveness; immunity; mandatory vaccination; natural language processing; neural network; public health; public health measures; public policy; social distancing; social media; social media analysis; vaccination; vaccine Entry Date(s): Date Created: 20231018 Date Completed: 20231124 Latest Revision: 20240110 Update Code: 20240110 PubMed Central ID: PMC10669926

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