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Modelling Spatial Behaviour in Music Festivals Using Mobile Generated Data and Machine Learning

Garcia, L; Lansley, G; Calnan, B; (2017) Modelling Spatial Behaviour in Music Festivals Using Mobile Generated Data and Machine Learning. In: GISRUK 2017 Proceedings. Geographical Information Science Research UK (GISRUK): Manchester, UK. Green open access

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Abstract

This study explores the utility of location data collected from a mobile phone app as a means of modelling spatial behaviour for consumer analysis, focusing on data from a music festival. Our aim was to harvest geo-temporal variables from the app data to model when individuals visit catering services across the site. Using Random Forest and Artificial Neural Networks machine learning algorithms, we presented an efficient means of simulating the popularity of bar areas within the festival site across time. The research demonstrates that with an appropriate methodology, mobile app data can provide useful insight for service provision planning.

Type: Proceedings paper
Title: Modelling Spatial Behaviour in Music Festivals Using Mobile Generated Data and Machine Learning
Event: The 25th GIS Research UK (GISRUK) Conference
Location: The University of Manchester
Dates: 18 April 2017 - 21 April 2017
Open access status: An open access version is available from UCL Discovery
Publisher version: http://huckg.is/gisruk2017/GISRUK_2017_paper_67.pd...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: crowd dynamics, spatio-temporal, mobile data, machine learning, feature engineering
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
URI: https://discovery.ucl.ac.uk/id/eprint/1556510
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