Location-Based Social Network Data for Exploring Spatial and Functional Urban Tourists and Residents Consumption Patterns

Ara: Journal of Tourism Research

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Title Location-Based Social Network Data for Exploring Spatial and Functional Urban Tourists and Residents Consumption Patterns
Datos de redes sociales basados en localización para explorar los patrones de consumo espaciales y funcionales de turistas urbanos y residentes
Creator Cerdan Schwitzguebel, Aurelie
Romero Bartomeus, Oriol
Subject urban tourism; Big Data; Yelp; spatial analysis; consumption pattern
turismo urbano; Big Data; Yelp; análisis espacial; patrones de consumo
Description Urban tourist destinations’ increasing popularity has been a catalyst for discussion about the tourist activity geographical circumscription. In this context, Big Data and more specifically location-based social networks (LBSN), appear as a valuable source of information to approach tourist and residents spatial interactions from a renewed perspective. This paper focuses on approaching similarities and differences between tourists and residents’ geographical and functional use of urban economic units. A user classificatory algorithm has been developed and applied on YELP’s Dataset for that purpose. A residents and tourists integration ratio has then been calculated and applied by types of businesses categories and their associated spatial distribution of the of 11 metropolitan areas provided in the sample: Champaign (Illinois, US), Charlotte (North Carolina, US), Cleveland (Ohio, US), Edinburgh (Scotland, UK), Las Vegas (Nevada, US), Madison (Wisconsin, US), Montreal (Quebec, CA), Pittsburgh (Pennsylvania, US), Phoenix (Arizona, US), Stuttgart (DE) and Toronto (Ontario, CA). Business category results show strong similarities in tourists and residents functional coincidence in the use of urban spaces and leisure offer, while there is a clear geographical concentration of activity for both user types in all analysed case studies.
La creciente popularidad de los destinos urbanos ha actuado como catalizador del debate sobre la delimitación geográfica de la actividad turística. En este contexto, el Big Data, y más específicamente las redes sociales que integran ubicación (LBSN), aparecen como una valiosa fuente de información para aproximarse a la interacción espacial entre turistas y residentes, desde una perspectiva renovada. Este artículo se centra en la aproximación a las similitudes y diferencias entre el uso geográfico y funcional de las unidades económicas urbanas, por parte de turistas y residentes. Para ello, se ha desarrollado y aplicado un algoritmo de clasificación de usuarios a un conjunto de datos de YELP. Se ha calculado también un ratio de integración entre turistas y residentes urbanos, posteriormente aplicado a los negocios georreferenciados y sus categorías funcionales, en las 11 áreas metropolitanas incluidas en la muestra: Champaign (Illinois, EEUU), Charlotte (Carolina del Norte, EEUU), Cleveland (Ohio, EEUU), Edimburgo (Escocia, GB), Las Vegas (Nevada, EEUU), Madison (Wisconsin, EEUU), Montreal (Quebec, CA), Pittsburg (Pennsylvania, EEUU), Phoenix (Arizona, EEU), Stuttgart (DE) and Toronto (Ontario, CA). Las categorías funcionales que agrupan los negocios muestran claras similitudes en cuanto a la coincidencia espacial entre turistas y residentes. Además, hay una clara concentración geográfica de la actividad para ambos grupos de usuario en todos los casos estudiados.
Publisher Universitat de Barcelona

Date 2019-01-21
Type info:eu-repo/semantics/article
Artículo revisado por pares
Format application/pdf
Identifier https://revistes.ub.edu/index.php/ara/article/view/27103
Source Ara: Revista de investigación en turismo; Vol. 8, Núm. 2 (2018); 32-52
Ara: Journal of Tourism Research; Vol. 8, Núm. 2 (2018); 32-52
Ara: Revista de Investigación en Turismo; Vol. 8, Núm. 2 (2018); 32-52
Language eng
Relation https://revistes.ub.edu/index.php/ara/article/view/27103/28462
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