Where you go reveals who you know: Analyzing social ties from millions of footprints

研究成果: Conference contribution

15 引文 斯高帕斯(Scopus)

摘要

This paper aims to investigate how the geographical footprints of users correlate to their social ties. While conventional wisdom told us that the more frequently two users co-locate in geography, the higher probability they are friends, we find that in real geo-social data, Gowalla and Meetup, almost all of the user pairs with friendships had never met geographically. In this sense, can we discover social ties among users purely using their geographical footprints even if they never met? To study this question, we develop a two-stage feature engineering framework. The first stage is to characterize the direct linkages between users through their spatial co-locations while the second is to capture the indirect linkages between them via a co-location graph. Experiments conducted on Gowalla check-in data and Meetup meeting events exhibit not only the superiority of our feature model, but also validate the predictability (with 70% accuracy) of detecting social ties solely from user footprints.

原文English
主出版物標題CIKM 2015 - Proceedings of the 24th ACM International Conference on Information and Knowledge Management
發行者Association for Computing Machinery
頁面1839-1842
頁數4
ISBN(電子)9781450337946
DOIs
出版狀態Published - 2015 十月 17
事件24th ACM International Conference on Information and Knowledge Management, CIKM 2015 - Melbourne, Australia
持續時間: 2015 十月 192015 十月 23

出版系列

名字International Conference on Information and Knowledge Management, Proceedings
19-23-Oct-2015

Other

Other24th ACM International Conference on Information and Knowledge Management, CIKM 2015
國家/地區Australia
城市Melbourne
期間15-10-1915-10-23

All Science Journal Classification (ASJC) codes

  • 決策科學 (全部)
  • 商業、管理和會計 (全部)

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