通过结构方程建模验证社交媒体传染病倾听概念框架的一部分
Shu-Feng Tsao1, Helen Chen1, Zahid A Butt1
1School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, Ontario, Canada.
EClinicalMedicine
|March 22, 2024
概括
社交媒体数据,包括推特情绪和参与度指标,可以预测COVID-19疫苗接种意图. 这项研究验证了使用Twitter数据和结构方程建模的SoMeIL框架.
科学领域:
- 公共卫生 公共卫生
- 计算社会科学 计算社会科学
- 卫生沟通健康沟通
背景情况:
- 影响COVID-19疫苗接种意图的因素已得到充分记录.
- 结构方程建模 (SEM) 是分析这些因素的常用统计技术.
- 社交媒体传染病倾听 (SoMeIL) 框架被提议将社交媒体数据与公共卫生行为联系起来.
研究的目的:
- 使用SEM和Twitter数据初步验证SoMeIL框架的组件.
- 检查利用Twitter数据在SEM研究中用于公共卫生的可行性.
- 从社交媒体参数推断COVID-19疫苗接种意图.
主要方法:
- 从加拿大多伦多和太华收集了2420条英语推特 (2021年3月8日至6月30日).
- 应用确认因素分析和SEM来验证SoMeIL框架.
- 分析了推特情绪,最喜欢的,转发的,以及用户指标 (关注者,列表).
主要成果:
- 情绪评分,推特最喜欢/转发,用户关注者/最喜欢/列表显示与COVID-19疫苗接种意图有显著的关联.
- 推特情绪具有最强的预测关系.
- 用户追随者数与疫苗接种意图的关系最弱.
结论:
- 反映在线反应的SoMeIL框架的组件可以初步推断COVID-19疫苗接种意图.
- 推特数据可用于用于公共卫生的SEM研究.
- 这项研究验证了SoMeIL框架内使用特定在线行为来了解接种疫苗的意图.
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