COVID-19;
vaccination;
stance analysis;
deep learning;
opinion mining;
natural language processing;
ACCEPTABILITY;
TWITTER;
TWEETS;
D O I:
10.3390/vaccines10060881
中图分类号:
R392 [医学免疫学];
Q939.91 [免疫学];
学科分类号:
100102 ;
摘要:
Vaccination has been proposed as one of the most effective methods to combat the COVID-19 pandemic. Since the day the first vaccine, with an efficiency of more than 90%, was announced, the entire vaccination process and its possible consequences in large populations have generated a series of discussions on social media. Whereas the opinions triggered by the administration of the initial COVID-19 vaccine doses have been discussed in depth in the scientific literature, the approval of the so-called 3rd booster dose has only been analyzed in country-specific studies, primarily using questionnaires. In this context, the present paper conducts a stance analysis using a transformer-based deep learning model on a dataset containing 3,841,594 tweets in English collected between 12 July 2021 and 11 August 2021 (the month in which the 3rd dose arrived) and compares the opinions (in favor, neutral and against) with the ones extracted at the beginning of the vaccination process. In terms of COVID-19 vaccination hesitance, an analysis based on hashtags, n-grams and latent Dirichlet allocation is performed that highlights the main reasons behind the reluctance to vaccinate. The proposed approach can be useful in the context of the campaigns related to COVID-19 vaccination as it provides insights related to the public opinion and can be useful in creating communication messages to support the vaccination campaign.
机构:
Univ Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
Fujian Med Univ, Sch Publ Hlth, Dept Epidemiol & Hlth Stat, Fuzhou 350122, Fujian, Peoples R ChinaUniv Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
Wong, Li Ping
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Alias, Haridah
Siaw, Yan-Li
论文数: 0引用数: 0
h-index: 0
机构:
Univ Malaya, Dept Educ Psychol Counselling, Fac Educ, Kuala Lumpur, MalaysiaUniv Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
Siaw, Yan-Li
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Muslimin, Mustakiza
Lai, Lee Lee
论文数: 0引用数: 0
h-index: 0
机构:
Univ Malaya, Dept Nursing, Fac Med, Kuala Lumpur, MalaysiaUniv Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
Lai, Lee Lee
Lin, Yulan
论文数: 0引用数: 0
h-index: 0
机构:
Fujian Med Univ, Sch Publ Hlth, Dept Epidemiol & Hlth Stat, Fuzhou 350122, Fujian, Peoples R ChinaUniv Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
Lin, Yulan
Hu, Zhijian
论文数: 0引用数: 0
h-index: 0
机构:
Fujian Med Univ, Sch Publ Hlth, Dept Epidemiol & Hlth Stat, Fuzhou 350122, Fujian, Peoples R ChinaUniv Malaya, Dept Social & Prevent Med, Ctr Epidemiol & Evidence Based Pract, Fac Med, Kuala Lumpur, Malaysia
机构:
Univ Calif Merced, Dept Psychol Sci, 5200 N Lake Rd, Merced, CA 95343 USA
Univ Calif Merced, Hlth Sci Res Inst, 5200 N Lake Rd, Merced, CA 95343 USA
Univ Jyvaskyla, Fac Sport & Hlth Sci, Jyvaskyla, Finland
Griffith Univ, Sch Appl Psychol, Brisbane, Qld, AustraliaUniv Calif Merced, Dept Psychol Sci, 5200 N Lake Rd, Merced, CA 95343 USA
Hagger, Martin S.
Hamilton, Kyra
论文数: 0引用数: 0
h-index: 0
机构:
Univ Calif Merced, Hlth Sci Res Inst, 5200 N Lake Rd, Merced, CA 95343 USA
Griffith Univ, Sch Appl Psychol, Brisbane, Qld, Australia
Griffith Univ, Menzies Hlth Inst Queensland, Brisbane, Qld, AustraliaUniv Calif Merced, Dept Psychol Sci, 5200 N Lake Rd, Merced, CA 95343 USA