دورية أكاديمية
Anti-vaccination attitude trends during the COVID-19 pandemic: A machine learning-based analysis of tweets
| العنوان: | Anti-vaccination attitude trends during the COVID-19 pandemic: A machine learning-based analysis of tweets |
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| المؤلفون: | Quyen G To, Kien G To, Van-Anh N Huynh, Nhung TQ Nguyen, Diep TN Ngo, Stephanie Alley, Anh NQ Tran, Anh NP Tran, Ngan TT Pham, Thanh X Bui, Corneel Vandelanotte |
| المصدر: | Digital Health, Vol 9 (2023) |
| بيانات النشر: | SAGE Publishing, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics |
| مصطلحات موضوعية: | Computer applications to medicine. Medical informatics, R858-859.7 |
| الوصف: | Objective Vaccine hesitancy has been ranked by the World Health Organization among the top 10 threats to global health. With a surge in misinformation and conspiracy theories against vaccination observed during the COVID-19 pandemic, attitudes toward vaccination may be worsening. This study investigates trends in anti-vaccination attitudes during the COVID-19 pandemic and within the United States, Canada, the United Kingdom, and Australia. Methods Vaccine-related English tweets published between 1 January 2020 and 27 June 2021 were used. A deep learning model using a dynamic word embedding method, Bidirectional Encoder Representations from Transformers (BERTs), was developed to identify anti-vaccination tweets. The classifier achieved a micro F1 score of 0.92. Time series plots and country maps were used to examine vaccination attitudes globally and within countries. Results Among 9,352,509 tweets, 232,975 (2.49%) were identified as anti-vaccination tweets. The overall number of vaccine-related tweets increased sharply after the implementation of the first vaccination round since November 2020 (daily average of 6967 before vs. 31,757 tweets after 9/11/2020). The number of anti-vaccination tweets increased after conspiracy theories spread on social media. Percentages of anti-vaccination tweets were 3.45%, 2.74%, 2.46%, and 1.86% for the United States, the United Kingdom, Australia, and Canada, respectively. Conclusions Strategies and information campaigns targeting vaccination misinformation may need to be specifically designed for regions with the highest anti-vaccination Twitter activity and when new vaccination campaigns are initiated. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2055-2076 20552076 |
| Relation: | https://doaj.org/toc/2055-2076 |
| DOI: | 10.1177/20552076231158033 |
| URL الوصول: | https://doaj.org/article/a14c3095e74346b7bb4a64e7c03c152c |
| رقم الأكسشن: | edsdoj.14c3095e74346b7bb4a64e7c03c152c |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20552076 |
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| DOI: | 10.1177/20552076231158033 |