{"title":"FluMapper:用于大规模基于位置的社交媒体数据分析的交互式网络地理信息系统环境","authors":"Anand Padmanabhan, Shaowen Wang, G. Cao, Myunghwa Hwang, Yanli Zhao, Zhenhua Zhang, Yizhao Gao","doi":"10.1145/2484762.2484821","DOIUrl":null,"url":null,"abstract":"Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].","PeriodicalId":426819,"journal":{"name":"Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"FluMapper: an interactive CyberGIS environment for massive location-based social media data analysis\",\"authors\":\"Anand Padmanabhan, Shaowen Wang, G. Cao, Myunghwa Hwang, Yanli Zhao, Zhenhua Zhang, Yizhao Gao\",\"doi\":\"10.1145/2484762.2484821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].\",\"PeriodicalId\":426819,\"journal\":{\"name\":\"Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2484762.2484821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2484762.2484821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FluMapper: an interactive CyberGIS environment for massive location-based social media data analysis
Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].