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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 | 2015/10/20 |
| 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 | Twitter-based urban area characterization by non-negative matrix factorization |
| 執筆形態 | その他 |
| 掲載誌名 | ACM International Conference Proceeding Series |
| 出版社・発行元 | Association for Computing Machinery |
| 巻・号・頁 | 20-23-,pp.128-135 |
| 著者・共著者 | Shoko Wakamiya,Ryong Lee,Yukiko Kawai,Kazutoshi Sumiya |
| 概要 | Due to the remarkable growth of various social networks boosted by the pervasive mobile devices, massive crowds can become social sensors which can share microbolgs on a variety of social situations and natural phenomena in urban space in real-time. In order to take advantages of the novel realm of crowd-sourced lifelogs to characterize urban areas, we attempt to explore characteristics of complex and dynamic urban areas by monitoring crowd behavior via location- based social networks. In particular, we define social conditions consisting of crowd's experiential features extracted from the analysis of Twitter-based crowd's lifelogs. Then, we explore latent characteristic faces of urban areas in term of 5-dimensional social conditions by applying Non-negative Matrix Factorization (NMF). In the experiments with massive geo-tagged tweets, we classify urban areas into representative groups based on their latent patterns which enable to comprehensively understand images of the urban areas fo- cusing on crowd's daily lives. |
| DOI | 10.1145/2837060.2837079 |