在COVID-19大流行期间,Twitter上与疫苗相关的内容的可信度
Samira Yousefinaghani1, Rozita Dara1, Alice Wang2
1School of Computer Science, University of Guelph, Guelph, Ontario, Canada.
PLOS global public health
|July 19, 2023
概括
在COVID-19疫苗宣传期间,Twitter上的错误信息与机器人类活动和更少的追随者有关. 了解这些模式可以帮助打击虚假叙述,并改善疫苗接种率.
科学领域:
- 公共卫生 公共卫生
- 社交媒体分析 社交媒体分析
- 计算社会科学 计算社会科学
背景情况:
- 推特是COVID-19疫苗信息交换的关键平台.
- 广泛的错误信息威胁到国家疫苗接种活动期间的疫苗接种.
研究的目的:
- 分析推特上的疫苗错误信息的内容和特征.
- 确定减轻疫苗错误信息的策略.
主要方法:
- 机器学习被用来检测疫苗相关推文中的错误信息.
- 分析了帐户特征,包括机器人类活动和参与度量.
主要成果:
- 错误信息在重要的疫苗公告期间达到顶峰.
- 散布错误信息的帐户显示出较高的机器人活动 (总体10%,15%的astroturf),并且拥有较少的追随者和验证的章.
- 与欧洲和北美相比,亚洲国家的错误信息比例较低.
结论:
- 了解虚假信息传播账户的特征对于制定有效的缓解策略至关重要.
- 针对机器人类活动和提高信息来源的可信度,可以有助于提高疫苗的信心和接种率.
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