In this paper we present a study sensing and analyzing an offline social network of participants at a large-scale music festival attended by 130,000+ participants, and featuring eight days of musical program on 6 stages. Spatio-temporal traces of participant mobility and interactions were collected from 33 Bluetooth scanners placed in strategic locations at the festival area to discover Bluetooth-enabled mobile phones carried by the participants. We employed an Infinite Relational Model (IRM) in order to analyze the collected data and to recover the structure of the network related to participants' music preferences. The obtained structure in the form of clusters of concerts and participants is then interpreted using meta-information about music genres, band origins, stages, and dates of the performances. We show that the concerts' clusters can be described by one or more of the meta-features, effectively revealing preferences of participants. Finally, we discuss the possibility of employing the described method and techniques for creating user-oriented applications and extending the sensing capabilities during large-scale events by introducing user involvement.
|Title of host publication||Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia : PDM '13|
|Publisher||Association for Computing Machinery|
|Publication status||Published - 2013|
|Event||1st ACM international workshop on Personal data meets distributed multimedia (PDM 2013) - Barcelona, Spain|
Duration: 22 Oct 2013 → …
|Workshop||1st ACM international workshop on Personal data meets distributed multimedia (PDM 2013)|
|Period||22/10/2013 → …|