Real-time spatio-temporal analysis of West Nile virus using Twitter data

R. Sugumaran, Jonathan Voss
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引用次数: 24

Abstract

West Nile virus (WNV) is one of the most geographically widespread arboviruses in the world with cases occurring on all continents except Antarctica. The goal of study is to understand a real-time spatial temporal WNV activity using Twitter data. In our study, we collected tweets for the entire world using Twitter Search API with tags #WestNileVirus, and #WNV from August 31, 2011. Collected tweets were stored, cleaned, and geocoded. The Google API was used to display information on the web. The changes per week showed that the numbers were relatively high from August through October then gradually slowed down from December through March. We also found a very large increase in tweet numbers from March and April. This may be due to unusual higher temperature and mosquito activities in March and April this year compared to previous years.
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利用Twitter数据对西尼罗河病毒进行实时时空分析
西尼罗病毒(WNV)是世界上地理分布最广的虫媒病毒之一,除南极洲外,所有大陆都有病例。研究的目的是利用Twitter数据了解WNV的实时时空活动。在我们的研究中,我们使用Twitter搜索API收集了2011年8月31日以来全世界范围内带有#西尼罗河病毒和#西尼罗河病毒标签的推文。收集到的tweet被存储、清理并进行地理编码。Google API用于在网络上显示信息。每周的变化表明,从8月到10月,这一数字相对较高,然后从12月到3月逐渐放缓。我们还发现,从3月到4月,推特数量大幅增加。这可能是由于与往年相比,今年三、四月的气温异常升高,蚊子活动频繁。
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