{"title":"利用Twitter数据对西尼罗河病毒进行实时时空分析","authors":"R. Sugumaran, Jonathan Voss","doi":"10.1145/2345316.2345361","DOIUrl":null,"url":null,"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.","PeriodicalId":400763,"journal":{"name":"International Conference and Exhibition on Computing for Geospatial Research & Application","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Real-time spatio-temporal analysis of West Nile virus using Twitter data\",\"authors\":\"R. Sugumaran, Jonathan Voss\",\"doi\":\"10.1145/2345316.2345361\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":400763,\"journal\":{\"name\":\"International Conference and Exhibition on Computing for Geospatial Research & Application\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference and Exhibition on Computing for Geospatial Research & Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2345316.2345361\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference and Exhibition on Computing for Geospatial Research & Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2345316.2345361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time spatio-temporal analysis of West Nile virus using Twitter data
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.