Sensing airports' traffic by mining location saring social services

John Garofalakis, Ioannis Georgoulas, Andreas Komninos, Periklis Ntentopoulos, Athanasios Plessas

Research output: Chapter in Book/Report/Conference proceedingChapter


Location sharing social services are popular among mobile users resulting in a huge social dataset available for researchers to explore. In this paper we consider location sharing social services’ APIs endpoints as “social sensors” that provide data revealing real world interactions, although in some cases, the number of recorded social data can be several orders of magnitude lower compared to the number of real world interactions. In the presented work we focus on check-ins at airports performing two experiments: one analyzing check-in data collected exclusively from Foursquare and another collecting additionally check-in data from Facebook. We compare the two popular location sharing social platforms’ check-ins and we show that for the case of Foursquare these data can be indicative of the passengers’ traffic, while their number is hundreds of times lower than the number of actual traffic observations.
Original languageEnglish
Title of host publicationCurrent Trends in Web Engineering
Subtitle of host publication15th International Conference, ICWE 2015 Workshops, NLPIT, PEWET, SoWEMine, Rotterdam, The Netherlands, June 23-26, 2015. Revised Selected Papers
EditorsFlorian Daniel, Oscar Diaz
Number of pages10
ISBN (Print)978-3-319-24799-1
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


  • location sharing services
  • foursquare
  • facebook
  • check-ins
  • ubiquitous social computing
  • information storage
  • information retrieval


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