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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2016/04/04 |
| 形態種別 | 研究論文（国際会議プロシーディングス） |
| 査読 | 査読あり |
| 標題 | Dynamic mapping of dense geo-tweets and web pages based on spatio-temporal analysis |
| 執筆形態 | その他 |
| 掲載誌名 | Proceedings of the ACM Symposium on Applied Computing |
| 出版社・発行元 | Association for Computing Machinery |
| 巻・号・頁 | 04-08-,pp.1170-1173 |
| 著者・共著者 | Yuanyuan Wang,Toyokazu Akiyama,Goki Yasui,Kazutoshi Sumiya,Yukiko Kawai,Yoshiharu Ishikawa |
| 概要 | Twitter evidently stirred a popular trend of personal update sharing. Twitter users can be kept up to date with current information from Twitter
however, users cannot obtain the most recent information, while they browse web pages since these are not updated in real time. Meanwhile, Twitter users are difficult to gain useful information about their current locations since these are often posted on web pages. To solve them, it is important to enrich traditional web pages with real time tweets. Therefore, we developed a novel tweet mapping system to support web and Twitter user communication through both the contents of tweets and web pages based on spatio-temporal analysis. Our system maps geo-tagged tweets to web pages by matching their location names, and categorizes tweets based on category names of floors from web pages according to different time frames. Thus, our system can effectively present the most related tweets and their summary to help users easily gain more detailed current situation in different time periods, and it also can effectively present messages from web users to help Twitter users immediately obtain useful information. In this paper, we discuss our proposed mapping method's effectiveness with our prototype system using dense tweets in urban areas. |
| DOI | 10.1145/2851613.2851985 |
| DBLP ID | conf/sac/WangYKASI16 |
| PermalinkURL | http://dblp.uni-trier.de/db/conf/sac/sac2016.html#conf/sac/WangYKASI16 |