Why people go to unfamiliar areas? Analysis of mobility pattern based on users' familiarity

Jungkyu Han, Hayato Yamana

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

Human mobility analysis with Location-Based Social Network (LBSN) data is the basis of personalized point-of-interest (POI) recommendations or location-aware advertisements. In addition to personal preference and spatiotemporal factors such as time and distance, personal context has a strong influence on mobility. An individual's familiarity with an area is an interesting context because it can bias the influence of certain factors. For example, the mobility patterns of two persons who have similar preferences are different when their familiarity with the area is different, even in the same area. In this paper, we analyze familiarity's effect on mobility patterns by using over 1.4 million check-ins gathered from Foursquare. The analysis indicates that there is a skewness of the visit time and visited venue distribution in unfamiliar areas. For instance, people go to unfamiliar areas on weekends; and venues for cultural experiences, such as museums, strongly contribute to the motivation of visit.

本文言語English
ホスト出版物のタイトル17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015 - Proceedings
編集者Matthias Steinbauer, Maria Indrawan-Santiago, Gabriele Anderst-Kotsis, Ismail Khalil
出版社Association for Computing Machinery, Inc
ISBN(電子版)9781450334914
DOI
出版ステータスPublished - 2015 12月 11
イベント17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015 - Brussels, Belgium
継続期間: 2015 12月 112015 12月 13

出版物シリーズ

名前17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015 - Proceedings

Other

Other17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015
国/地域Belgium
CityBrussels
Period15/12/1115/12/13

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 情報システム
  • コンピュータ サイエンスの応用

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