Deep Learning Analysis of COVID-19 Vaccine Hesitancy and Confidence Expressed on Twitter in 6 High-Income Countries: Longitudinal Observational Study

被引:5
|
作者
Zhou, Xinyu [1 ,2 ,3 ]
Song, Suhang [4 ]
Zhang, Ying [1 ,2 ]
Hou, Zhiyuan [1 ,2 ,5 ]
机构
[1] Fudan Univ, Sch Publ Hlth, Shanghai, Peoples R China
[2] Fudan Univ, Global Hlth Inst, Shanghai, Peoples R China
[3] Yale Sch Publ Hlth, Dept Biostat, New Haven, CT USA
[4] Univ Georgia, Coll Publ Hlth, Dept Hlth Policy & Management, Athens, GA USA
[5] Fudan Univ, Sch Publ Hlth, 130 Dongan Rd, Shanghai 200032, Peoples R China
关键词
COVID-19; vaccine; hesitancy; confidence; social media; machine learning;
D O I
10.2196/49753
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: An ongoing monitoring of national and subnational trajectory of COVID-19 vaccine hesitancy could offer support in designing tailored policies on improving vaccine uptake. Objective: We aim to track the temporal and spatial distribution of COVID-19 vaccine hesitancy and confidence expressed on Twitter during the entire pandemic period in major English-speaking countries. Methods: We collected 5,257,385 English-language tweets regarding COVID-19 vaccination between January 1, 2020, and June 30, 2022, in 6 countries-the United States, the United Kingdom, Australia, New Zealand, Canada, and Ireland. Transformer-based deep learning models were developed to classify each tweet as intent to accept or reject COVID-19 vaccination and the belief that COVID-19 vaccine is effective or unsafe. Sociodemographic factors associated with COVID-19 vaccine hesitancy and confidence in the United States were analyzed using bivariate and multivariable linear regressions. Results: The 6 countries experienced similar evolving trends of COVID-19 vaccine hesitancy and confidence. On average, the prevalence of intent to accept COVID-19 vaccination decreased from 71.38% of 44,944 tweets in March 2020 to 34.85% of 48,167 tweets in June 2022 with fluctuations. The prevalence of believing COVID-19 vaccines to be unsafe continuously rose by 7.49 times from March 2020 (2.84% of 44,944 tweets) to June 2022 (21.27% of 48,167 tweets). COVID-19 vaccine hesitancy and confidence varied by country, vaccine manufacturer, and states within a country. The democrat party and higher vaccine confidence were significantly associated with lower vaccine hesitancy across US states. Conclusions: COVID-19 vaccine hesitancy and confidence evolved and were influenced by the development of vaccines and viruses during the pandemic. Large-scale self-generated discourses on social media and deep learning models provide a cost-efficient approach to monitoring routine vaccine hesitancy.
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页数:14
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