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

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Título: Measuring urban activities using Foursquare data and network analysis: a case study of Murcia (Spain)
Autor/es: Agryzkov, Taras | Martí Ciriquián, Pablo | Tortosa, Leandro | Vicent, Jose F.
Grupo/s de investigación o GITE: Análisis y Visualización de Datos en Redes (ANVIDA) | Urbanística y Ordenación del Territorio en el Espacio Litoral
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Edificación y Urbanismo
Palabras clave: Urban analysis | Social networks analysis | Street networks | PageRank algorithms | Data visualization
Área/s de conocimiento: Ciencia de la Computación e Inteligencia Artificial | Urbanística y Ordenación del Territorio
Fecha de publicación: 2017
Editor: Taylor & Francis
Cita bibliográfica: International Journal of Geographical Information Science. 2017, 31(1): 100-121. doi:10.1080/13658816.2016.1188931
Resumen: 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.
Patrocinador/es: This work was partially supported by Spanish Govern, Ministerio de Economía y Competividad, the reference number of which is TIN2014-53855-P.
ISSN: 1365-8816 (Print) | 1365-8824 (Online)
DOI: 10.1080/13658816.2016.1188931
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2016 Informa UK Limited, trading as Taylor & Francis Group
Revisión científica: si
Versión del editor:
Aparece en las colecciones:INV - ANVIDA - Artículos de Revistas
INV - UOTEL - Artículos de Revistas

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