利用人工智能从X (Twitter) 社交网络中提取有关世卫组织COVID-19疫苗接种声明后的见解
Ali S Abed Al Sailawi1,2, Mohammad Reza Kangavari1
1School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran.
AIMS public health
|July 19, 2024
概括
人工智能 (AI) 分析了1550万条COVID-19疫苗接种推文. 在了解全球公众对疫苗接种情绪和疫苗接种后经济复苏方面,BiLSTM模型表现出卓越的表现.
科学领域:
- 计算社会科学 计算社会科学
- 公共卫生信息学 公共卫生信息学
- 流行病学中的人工智能
背景情况:
- 随着COVID-19的流行,在网上引发了广泛的讨论,特别是关于疫苗接种的问题.
- 在世界卫生组织 (WHO) 宣布疫苗接种后,分析公众对疫苗接种的情绪对于危机管理至关重要.
- 有限的研究专注于人工智能驱动的对X (以前的Twitter) 等社交媒体平台上与疫苗接种相关的言论的分析.
研究的目的:
- 利用人工智能 (AI) 来分析X (以前的Twitter) 数据对COVID-19疫苗接种的公众情绪.
- 在世卫组织宣布疫苗接种后,确定公众论的全球和区域趋势.
- 通过数据驱动的洞察力增强公共卫生危机管理战略.
主要方法:
- 从2020年12月到2021年7月收集了1550万条推特,这些推特使用了#疫苗和#冠状病毒等关键词.
- 采用并比较了三个机器学习模型:BiLSTM,FFNN和CNN用于情绪分析.
- 采用BiLSTM,其F1得分为0.84,精度为0.85,回忆率为0.83.
主要成果:
- 与FFNN和CNN相比,BiLSTM在情绪分类方面表现优越.
- 全球情绪可视化显示,人们对疫苗接种后经济复苏的看法存在显著的区域差异.
- 东欧国家表达了积极的情绪,而中国和美国表达了关于疫苗接种后经济复苏的负面情绪.
结论:
- 人工智能,特别是BiLSTM模型,对于分析大规模的社交媒体关于公共卫生主题的数据是有效的.
- 了解区域情绪差异对于有针对性的公共卫生干预和危机沟通至关重要.
- 该研究为公众对COVID-19疫苗接种及其经济影响的看法提供了宝贵的见解.
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