@inbook {80,
	title = {Sensing Airports{\textquoteright} Traffic by Mining Location Sharing Social Services},
	booktitle = {Current Trends in Web Engineering: 15th International Conference, ICWE 2015 Workshops, NLPIT, PEWET, SoWEMine, Rotterdam, The Netherlands, June 23-26, 2015. Revised Selected Papers},
	volume = {9396},
	number = {LNCS},
	year = {2015},
	pages = {131-140},
	publisher = {Springer},
	organization = {Springer},
	address = {Cham, Switzerland},
	abstract = {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{\textquoteright} APIs endpoints as {\textquotedblleft}social sensors{\textquotedblright} 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{\textquoteright} check-ins and we show that for the case of Foursquare these data can be indicative of the passengers{\textquoteright} traffic, while their number is hundreds of times lower than the number of actual traffic observations.},
	keywords = {Check-ins, Location sharing services, social networks, Ubiquitous social computing},
	doi = {10.1007/978-3-319-24800-4},
	author = {John Garofalakis and Ioannis Georgoulas and Andreas Komninos and Periklis Ntentopoulos and Athanasios Plessas}
}
@conference {67,
	title = {Location sharing services as sensors for analyzing airports{\textquoteright} traffic},
	booktitle = {11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous 2014)},
	year = {2014},
	month = {12/2014},
	abstract = {Location sharing services can be seen as {\textquotedblleft}social sensors{\textquotedblright} that provide data revealing real world interactions. In this paper, we examine the case of foursquare check-ins at airports and we show that these data can be indicative of the passengers{\textquoteright} traffic, while their number is hundreds of times lower than the number of actual traffic observations.  },
	keywords = {Check-ins, Location sharing services, social networks, Ubiquitous social computing.},
	doi = {10.4108/icst.mobiquitous.2014.257878},
	author = {John Garofalakis and Ioannis Georgoulas and Andreas Komninos and Periklis Ntentopoulos and Athanasios Plessas}
}
@conference {63,
	title = {This is How We Roll: Cultural Traits in Check-in Behaviour},
	booktitle = {Seventh IEEE International Workshop on Selected Topics in Wireless and Mobile computing (STWiMob 2014)},
	year = {2014},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Larnaca, Cyprus},
	abstract = {We describe our analysis of three months worth of collected human-physical environment interactions (foursquare check-in) data for two European cities: a medium-sized city in the Mediterranean and a larger city in North West Europe. Our analysis shows that though the data generated by the citizens is scarce (i.e. on average less than 15 users checked in at any time during the day), nevertheless they can closely reflect a city{\textquoteright}s dynamics. The paper also discusses the strong suggestion of emergent cultural traits from the data and its use to power new pervasive applications based on human-physical interaction.},
	keywords = {Check-ins, human-physical interaction, urban social context},
	doi = {10.1109/WiMOB.2014.6962175},
	author = {Andreas Komninos and Jeries Besharat and John Garofalakis and Dimitrios Michelakis}
}
