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
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