Measuring urban activities using Foursquare data and network analysis: a case study of Murcia (Spain)

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Title: Measuring urban activities using Foursquare data and network analysis: a case study of Murcia (Spain)
Authors: Agryzkov, Taras | Martí Ciriquián, Pablo | Tortosa, Leandro | Vicent, Jose F.
Research Group/s: Análisis y Visualización de Datos en Redes (ANVIDA) | Urbanística y Ordenación del Territorio en el Espacio Litoral
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Edificación y Urbanismo
Keywords: Urban analysis | Social networks analysis | Street networks | PageRank algorithms | Data visualization
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial | Urbanística y Ordenación del Territorio
Issue Date: 2017
Publisher: Taylor & Francis
Citation: International Journal of Geographical Information Science. 2017, 31(1): 100-121. doi:10.1080/13658816.2016.1188931
Abstract: Among social networks, Foursquare is a useful reference for identifying recommendations about local stores, restaurants, malls or other activities in the city. In this article, we consider the question of whether there is a relationship between the data provided by Foursquare regarding users’ tastes and preferences and fieldwork carried out in cities, especially those connected with business and leisure. Murcia was chosen for case study for two reasons: its particular characteristics and the prior knowledge resulting from the fieldwork. Since users of this network establish, what may be called, a ranking of places through their recommendations, we can plot these data with the objective of displaying the characteristics and peculiarities of the network in this city. Fieldwork from the city itself gives us a set of facilities and services observed in the city, which is a physical reality. An analysis of these data using a model based on a network centrality algorithm establishes a classification or ranking of the nodes that form the urban network. We compare the data extracted from the social network with the data collected from the fieldwork, in order to establish the appropriateness in terms of understanding the activity that takes place in this city. Moreover, this comparison allows us to draw conclusions about the degree of similarity between the preferences of Foursquare users and what was obtained through the fieldwork in the city.
Sponsor: This work was partially supported by Spanish Govern, Ministerio de Economía y Competividad, the reference number of which is TIN2014-53855-P.
URI: http://hdl.handle.net/10045/73316
ISSN: 1365-8816 (Print) | 1365-8824 (Online)
DOI: 10.1080/13658816.2016.1188931
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2016 Informa UK Limited, trading as Taylor & Francis Group
Peer Review: si
Publisher version: http://dx.doi.org/10.1080/13658816.2016.1188931
Appears in Collections:INV - ANVIDA - Artículos de Revistas
INV - UOTEL - Artículos de Revistas

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