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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 | 2015/08/10 |
| 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 | Portraying collective spatial attention in Twitter |
| 執筆形態 | その他 |
| 掲載誌名 | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining |
| 出版社・発行元 | Association for Computing Machinery |
| 巻・号・頁 | 2015-,pp.39-48 |
| 著者・共著者 | Émilien Antoine,Adam Jatowt,Shoko Wakamiya,Yukiko Kawai,Toyokazu Akiyama |
| 概要 | Microblogging platforms such as Twitter have been recently frequently used for detecting real-time events. The spatial component, as reflected by user location, usually plays a key role in such systems. However, an often neglected source of spatial information are location mentions expressed in tweet contents. In this paper we demonstrate a novel visualization system for analyzing how Twitter users collectively talk about space and for uncovering correlations between geographical locations of Twitter users and the locations they tweet about. Our exploratory analysis is based on the development of a model of spatial information extraction and representation that allows building effective visual analytics framework for large scale datasets. We show visualization results based on half a year long dataset of Japanese tweets and a four months long collection of tweets from USA. The proposed system allows observing many space related aspects of tweet messages including the average scope of spatial attention of social media users and variances in spatial interest over time. The analytical framework we provide and the findings we outline can be valuable for scientists from diverse research areas and for any users interested in geographical and social aspects of shared online data. |
| DOI | 10.1145/2783258.2783418 |
| DBLP ID | conf/kdd/AntoineJWKA15 |
| PermalinkURL | http://dblp.uni-trier.de/db/conf/kdd/kdd2015.html#conf/kdd/AntoineJWKA15 |