Characterizing Urban Landscapes Using Geolocated Tweets

Frías-Martínez, Vanessa; Soto, Víctor; Hohwald, Heath; Frı́as-Martı́nez, Enrique

doi:10.1109/socialcom-passat.2012.19

Cited by 160 publications

(137 citation statements)

References 14 publications

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“…Twitter's daily use profiles serve to classify the space according to the type of dominant activity, whether business, leisure/weekend, nightlife and residential (Frias-Martinez et al, 2012). Geolocated tweets have also been used to analyse the degree of social mixing in the use of space by tracking the movement of social groups in highly segregated cities such as Río de Janeiro (Netto et al, 2005) and Louisville (Shelton et al, 2015).…”

Section: Being Connected: Twittermentioning

confidence: 99%

Tourists' digital footprint in cities: Comparing Big Data sources

et al. 2018

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Abstract.-There is little knowledge available on the spatial behaviour of urban tourists, and yet tourists generate an enormous quantity of data (Big Data) when they visit cities. These data sources can be used to track their presence through their activities. The aim of this paper is to analyse the digital footprint of urban tourists through Big Data. Unlike other papers that use a single data source, this article examines three sources of data to reflect different tourism activities in cities: Panoramio (sightseeing), Foursquare (consumption), and Twitter (being connected). Tourist density in the three data sources is compared via maps, correlation analysis (OLS) and spatial self-correlation analysis (Global Moran's I statistic and LISA). Finally the data are integrated using cluster analysis and combining the spatial clusters identified in the LISA analysis in the different data sources. The results show that the data from the three activities are partly spatially redundant and partly complementary, and allow the characterisation of multifunction tourist spaces (with several activities) and spaces specialising in one or various activities (for example, sightseeing and consumption). The case study analysed (Madrid) reveals a significant presence of tourists in the city centre, and increasing specialisation from the centre outwards towards the periphery. The main conclusion of the paper is that it is not sufficient to use one data source to analyse the presence of tourists in cities; several must be used in a complementary manner.

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Section: Being Connected: Twittermentioning

confidence: 99%

Tourists' digital footprint in cities: Comparing Big Data sources

et al. 2018

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“…In the representation model, SMGI may be used to facilitate the description of a geographic context, providing experiential knowledge that is usually dismissed in official information and integrating A-GI with a pluralist vision of geographic phenomena, which may be used to identify social and cultural dynamics affecting the area. For example, SMGI from several Location-Based Social Networks (LBSNs) has been used to identify the most appreciated Points of Interest (POIs) and landmarks in a study area (Jankowski et al, 2010), the pedestrian paths in the historical centre of a city, the neighbourhoods featuring the lowest number of services and the different land uses in an urban environment (Frias-Martinez et al, 2012), and to classify urban areas (Noulas et al, 2011).…”

Section: The Geodesign Approach: Opportunities Arising From Vgi and Smgimentioning

confidence: 99%

Opportunities for Volunteered Geographic Information Use in Spatial Planning

Nikšič

Campagna

Massa

et al. 2017

Mapping and the Citizen Sensor

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This chapter highlights two types of georeferenced User-Generated Content (geo-UGC) that show considerable potential for fruitful usage in spatial planning in practice: Volunteered Geographic Information (VGI) and Social Media Geographic Information (SMGI). By describing selected case studies, the chapter illustrates how geo-UGC can be used at different stages of spatial planning processes, supporting a more pluralist understanding of places, fostering the collaboration between decision-makers and contributing to a more participatory practice in spatial planning. The Geodesign approach is used as the framework for underpinning the discussion. Selected case studies developed by the authors are presented showing how geo-UGC can be beneficial for building knowledge on current urban and territorial dynamics, for identifying possible alternative futures and for finding agreement on preferable future developments. In all the selected cases, large numbers of users were involved

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“…Así, Frías-Martínez et al (2012) utilizaron la variación espaciotemporal de los tweets para diferenciar el uso del suelo urbano e identificar los principales puntos de interés (monumentos) de Nueva York. Por otro lado se ha constatado que el perfil horario de los tweets es diferente según se trata de ocupados (mayor cantidad de tweets enviados en las primeras horas de la mañana) y desempleados (más tweets al final de la tarde y primeras horas de la noche), con lo Revista de Estudios Andaluces, vol.…”

Section: Redes Sociales: Twitter Y Foursquareunclassified