在澳大利亚维多利亚州,在分阶段的COVID-19限制期间,基于Twitter的地理位置定位人口流动性
Thin Nguyen1, Sunil Gupta1, Jaishankar Raman2
1Applied Artificial Intelligence Institute (A2I2), Deakin University, Melbourne, VIC, Australia.
概括
地理标记的推特数据为2019年冠状病毒病 (COVID-19) 流行期间的人口流动性变化提供了实时洞察力. 这项研究表明,它有潜力跟踪公共卫生限制对流动性的影响.
科学领域:
- * * 公共卫生 公共卫生
- * 数据科学数据科学
- * 流行病学 流行病学
背景情况:
- *2019年冠状病毒病 (COVID-19) 流行病需要前所未有的公共卫生干预措施,包括分阶段限制.
- *了解人口流动性对于评估这些措施的有效性至关重要.
- * 传统的移动数据收集方法可能很慢,缺乏实时细节性.
研究的目的:
- *使用地理标记的Twitter数据开发和评估一个流动性指数.
- *分析在COVID-19限制期间维多利亚州人口流动的变化.
- * 探索社交媒体数据对实时公共卫生监测的有用性.
主要方法:
- *从维多利亚州收集和地理编码推特数据.
- * 基于地理标记的推文创建人口流动性指数.
- *分析与COVID-19限制时间相关的流动性指数趋势.
主要成果:
- *初步证据表明,地理标记的Twitter数据可以生成实时移动指数.
- * 移动指数的观察变化与COVID-19限制的实施和放松相对应.
- *这些数据提供了有关大流行期间人口流动模式的见解.
结论:
- * 地理标记的推特数据是实时评估人口流动性的有希望的工具.
- *这种方法可以为公共卫生战略和评估非药物干预提供信息.
- * 进一步的研究可以为更广泛的公共卫生应用改进这种方法.
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