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Using Data from Foursquare Web Service to Represent the Commercial Activity of a City.
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This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues –especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people's interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.
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... Most LBSNs give a unique identity number to each and B Sonia Khetarpaul sonia.khetarpaul@snu.edu.in 1 Shiv Nadar University, Delhi NCR, India every distinct location. Typically, a user checks-in to a particular location by using a smart mobile phone or a tablet. ...
... LBSN data retrieved about specific locations reveal important details about the everyday urban life in those places. LBSN data provide a representative sample of citizen preferences and mobility activities, which may sometimes biased towards users interest [1,32]. Since users do not share their personal details, therefore, the sample data cannot be rigorously characterised in terms of user profiles. ...
Analyzing and understanding the movement patterns of the citizen’s with in a city, plays an important role in urban and transportation planning. Though many recent research papers focused on mining LBSN services data and performed in-depth analysis of users’ mobility patterns and their impact on their social inter-connections and friends. This paper focuses on understanding the Citizen’s movement patterns of socially interconnected users in friendship networks, by analyzing their spatial-temporal footprints/check-ins. The aim of this paper is to find the impact of structural patterns hidden in the nodes of a friendship network and external environment changes on the check-in patterns of the users. First, we classify each spatial check-in event based on its cause into either self reinforcing behavior or social influence or external stimulus. Then we mine the collective behavior of the all the users during some special events.
... In this way, it is possible to visualize, analyze, and operate spatially with information uploaded to an LBSN. Mining LBSNs is a crucial step for general data analysis (Chen, Härdle and Unwin, 2008;Agryzkov et al., 2015), which is presented as a complementary or alternative method to traditional research on mobility, activity patterns, urban complexity, social preferences, or perception (Kheiri, Karimipour and Forghani, 2015). Eventually, it can also be used to define guidelines for further urban design interventions (Corinna, Riccardo and Ludovica, 2014;Cerrone, Lehtovouri and Pau, 2015). ...
... This is precisely the definition of crowd-sourced big data according to Jiang et al. (2016): a large amount of data obtained from application users who share info from their devices, with an individual level definition for each point in time and space, and other associated data (Schwartz and Halegoua, 2014;Jiang et al., 2016); acknowledging a major potential in the possibility of operating on a granular scale, and a largescale simultaneously (Luo et al. 2016). Thus, location-based services in the field of urban planning aim to offer researchers a representative sample of what happens in physical reality (Agryzkov et al., 2015), as well as to publicize the meta-dynamics or urban social processes beyond the physical form of cities (Cerrone 2016). ...
The following work presents several trans-disciplinary resources for understanding cities beyond just their physical form and spatial processes. The conceptualization of cities from a top-down, modern and post- modern approach to the form-function duality lacks multiple dimensions, which need to be studied in order to gain a proper understanding of how contemporary urban societies perform nowadays. Instead, this work considers settlements as a set of an infinite number of individual perceptions and experiences, which construct overlapping layers of hidden and intangible information that shape cities as complex systems.
Social relations that are moving progressively to the virtual realm are becoming major factors in decision- making and location choices by citizens. This definition of a city’s hidden image is developed through the study of data retrieved from online servers. To do so, this work focuses on spatial and temporal activity patterns, values of certain places and their quantitative weight within the urban fabric, the distribution and nature of places, the observation of people’s perception of certain places through the representation of activities captured by pictures posted online, or several other theoretical and methodological approaches under the umbrella of crowd-sourced data in the city.
See full text: http://hdl.handle.net/10045/108227
... Foursquare has already been used in urban studies with diverse objectives, such as understanding city dynamics (Cranshaw et al., 2021), analysing economic diversity (Agryzkov et al., 2015), complexity (Lo´pez Baeza et al., 2017), popularity of certain places (Martı´et al., 2017) or the placeidentity of new developments (Carpio-Pinedo and Lo´pez- Baeza, 2021). However, to the best of our knowledge, this type of data has not been used to study the geography of LGBTQ + urban spaces yet. ...
LGBTQ + neighbourhoods and venues in our cities have fulfilled many vital functions for LGBTQ + people and for society as a whole. Generally identified through the concentration of consumption spaces that host meetings between LGBTQ + people, they have a great symbolic value in the fight for their rights and against intolerance. At a time when doubts arise about their future, there are far fewer spatial, quantitative and systematic analyses of these concentration patterns, especially from an international and comparative approach to the phenomenon. The digitisation of our daily lives generates big data that make possible avenues of research that were hitherto impossible, not only in detail and extent, but also in the nature of the questions to answer. In this article, we analyse Foursquare location-based social big data to quantify and spatialise clustering patterns of queer places and symbolic capital in four LGBTQ + neighbourhoods (Castro in San Francisco, Soho in London, Chueca in Madrid and Le Marais in Paris) and take similar spaces with no LGBTQ + identity as a reference. In doing so, the greater accumulation of symbolic capital in LGBTQ + spaces is revealed and measured in these four cities. In future, similar studies could capture trends like the gentrification of these environments, to help policy-makers make data-driven decisions to promote more inclusive and diverse cities.
... However, others have found that LBSN data is in fact representative (Morstatter et al., 2013;Tufekci, 2014;Agryzkov et al., 2015;Barberá and Rivero, 2015;Martí, Serrano-Estrada and Nolasco-Cirugeda, 2017). Given the significantly larger user base, and broader applications of Google Places than the previously studied platforms, representativeness may be less of an issue for Google Places data. ...
Public participation is an important element for ensuring sustainable urban development, yet it is often under-utilized due to the time and cost of gathering and analyzing user inputs. Big Data and Artificial Intelligence are emerging tools in the field of urban research and practice that could help bridge some of these gaps and provide near real-time insights on user satisfaction and preferences with the built environment.
This dissertation studies the use of online reviews to better understand urban parks, analyzing Google Maps user reviews and ratings from 12,689 urban parks across 99 cities in the United States, representing 6,859,156 reviews. It seeks insights from two key datapoints (online user reviews and user ratings) to test the utility and implications of the use of Big Data and Artificial Intelligence to better understand urban park user preferences. It researches i) the predictor relationship between The Trust for Public Land’s ParkScore Index attributes and Google Maps user satisfaction ratings at the citywide park system scale; and ii) utilizes Natural Language Processing (sentiment, keyword and topic analysis) - a branch of Artificial Intelligence that applies machine learning to study key determinants of user satisfaction- to understand park user interests, likes and dislikes.
The results suggest that this volunteered geographic information may be a complementary tool for monitoring and comparing park user preferences and informing planning, management and investment decisions, however online datasets have a number of important limitations that must be considered when analyzing and applying findings to ensure questions of representativeness, reliability and equity are considered.
... Los datos de Foursquare han sido ya empleados con diferentes objetivos dentro de la disciplina urbanística, desde el análisis de la diversidad de actividad económica en la ciudad (Agryzkov et al., 2015) hasta la preferencia por diferentes espacios (Martí, Serrano-Estrada, & Nolasco-Cirugeda, 2017) o su popularidad (Komninos, Stefanis, Plessas, & Besharat, 2013;Serrano-Estrada, Salvador, & Álvarez Álvarez, 2014). Cerrone, López Baeza y Lehtovuori (2018) han utilizado Foursquare como base para una clasificación de actividades sobre la que también han desarrollado un índice de complejidad económica, entropía de actividades y tipos de actividad por tramo de calle (López Baeza, Cerrone, & Männigo, 2017). ...
Este trabajo propone un acercamiento al estudio de la producción de identidad y sentimiento de apropiación espacial en determinados entornos urbanos. Identidad y apropiación son estudiados desde el análisis de hitos y topónimos, utilizando para ello big data desde Foursquare, red social en la cual los usuarios publican sus visitas a lugares. Se analizan varios crecimientos urbanos de la reciente burbuja inmobiliaria en el Área Metropolitana de Madrid (1990-2012), sospechosos de falta de identidad por la reciente y rápida urbanización, así como por posibles mecanismos de simplificación del tejido urbano. El análisis valora diferentes tipos de crecimiento, revelando una correspondencia entre la tipología morfológica de los desarrollos y el tipo de lugares que constituyen hitos en ellas, así como con la aparición de topónimos, destacando ciertos lugares como elementos potenciales generadores de identidad social urbana.
... Secondly, there are contrasting opinions about whether LBSNs represent the entire population. Some studies argue that LBSN data provide a representative sample of citizen preferences, opinions and activities (Agryzkov et al., 2015;Barbera & Rivero, 2015;Martí, Serrano-Estrada, & Nolasco-Cirugeda, 2017;Morstatter, Pfeffer, Liu, & Carley, 2013;Tufekci, 2014), given the increasing diversity of user profiles (Pew Research Center, 2017). Others claim that LBSN users are not necessarily a representative sample (Quercia, Aiello, Schifanella, & Davies, 2015a, 2015b based on the assumption that social media users comprise only part of the population whose use of a particular social network tends to be aligned to a specific interest. ...
Analysing the city through data retrieved from Location Based Social Networks (LBSNs) has received considerable attention as a promising method for applied research. However, the use of these data is not without its challenges and has given rise to a stream of polemical arguments over the validity of this source of information. This paper addresses the challenges and opportunities as well as some of the limitations and biases associated with the collection and use of LBSN data from Foursquare, Twitter, Google Places, Instagram and Airbnb in the context of urban phenomena research. The most recent research that uses LBSN data to understand city dynamics is presented. A method is proposed for LBSN data retrieval, selection, classification and analysis. In addition, key thematic research lines are identified given the data variables offered by these LBSNs. A com-
prehensive and descriptive framework for the study of urban phenomena through LBSN data is the main con-
tribution of this study.
Locative social media networks as open sources of data allow researchers and professionals to acknowledge which city places are preferred, used and livable. Following this hypothesis, this paper proposes a methodology to identify successful public spaces – plazas – through the location-based social media network Foursquare and to analyze their urban position using morphological and historical cartographies. The overall methodology comprises three stages. First, the most important cities of the province of Alicante were selected. Second, the most relevant plaza of each city was identified using data retrieved from the social network Foursquare. Finally, the location of each plaza is analyzed in relation to the historic center and the main axes of the city. Possible correlations between their urban location and their vibrant character were subsequently identified. Two findings have emerged from this study: (a) a strong spatial relationship exists between the most successful plazas and the historic city center, which reinforces their traditional social character; and (b) all plazas share two similar traits, their location within the urban network and their proximity to the main axes of the city.
El análisis del espacio público urbano a partir de su dimensión perceptual ha sido, tradicionalmente, un recurso
fundamental para reconocer qué características físicas lo diferencian y le confieren actividad y vitalidad. Esta
aproximación es particularmente relevante en entornos urbanos transformados. Conocer la percepción social
sobre el espacio público permite valorar en qué medida las acciones realizadas modifican las dinámicas urbanas.
Bajo esta consideración, el objetivo de este trabajo es estudiar la vida urbana tras la transformación de la Calle San
Francisco, en Alicante, España, en un espacio lúdico caracterizado por la implantación de una serie de setas
gigantes. Para ello, se definieron y evaluaron tres indicadores de vida pública: las actividades económicas en la
edificación antes y después de la intervención; el uso social del espacio proyectado; y, la imagen pública —o
imagen percibida—resultante. Se propone una metodología híbrida que combina los datos recogidos en un estudio
de campo con los datos provenientes de fuentes de base tecnológica, concretamente, de la red social Instagram y
del servicio web Google Street View. Los resultados obtenidos ponen de manifiesto que la utilización de datos
offline y online permite confirmar, complementar o cuestionar las deducciones parciales de cada uno de los
métodos, ratificando así que la transformación de la Calle San Francisco ha modificado sustancialmente no sólo
su identidad física, sino sobre todo la imagen colectiva del espacio con relación a la del resto de la ciudad. En
definitiva, este trabajo evidencia la pertinencia de incorporar técnicas de base tecnológica para entender la
complejidad de las relaciones sociales, físicas y virtuales, que se producen como consecuencia de la
transformación de un espacio urbano.
La teoría construida en torno a la idea de conseguir ciudades más sostenibles apuesta, entre otras cuestiones, por una diversidad de actividades tal que sea capaz de producir realidades urbanas funcionalmente complejas.
Esta complejidad, entendida desde un punto de vista urbano, incide positivamente en diferentes aspectos. Por una parte, fomenta los desplazamientos peatonales entre actividades próximas lo que repercute en un menor protagonismo del vehículo privado en las ciudades. Por otra parte, incrementa la animación del espacio urbano haciéndolo más atractivo. Por estas y otras cuestiones, resulta de interés estudiar la diversidad de actividades en la ciudad y particularmente en el ámbito turístico dada la fuerte especialización que mantienen las ciudades que se encuentran intensamente influidas por este fenómeno y dado el impacto que un buen grado de complejidad tiene sobre la mejora de la experiencia turística.
Con el fin de hacer un estudio aplicado de los indicadores de complejidad urbana en el ámbito turístico se escoge la ciudad de Benidorm como ejemplo paradigmático del turismo de sol y playa en el litoral mediterráneo español. Diversos autores coinciden en que Benidorm presenta un modelo turístico ampliamente consolidado y profundamente especializado en las funciones propias de la industria del ocio. Así, se plantea el análisis de dos espacios funcionales relevantes en cuanto al turismo como son los paseos marítimos de Levante y Poniente.
Como metodología de análisis se propone utilizar información existente en internet para, a través de las actividades recogidas en redes sociales - concretamente Foursquare y Google Places-, describir y comparar la complejidad funcional que configura ambos espacios. La descarga y georreferenciación de la información obtenida servirá para dos propósitos. En primer lugar, establecer una categorización que permita evaluar en qué medida existe la diversidad de actividades y en qué medida existe una especialización de funciones y, en segundo lugar, estudiar la relación que existe entre los datos obtenidos y los planteados por algunos indicadores de sostenibilidad publicados en relación al estudio de la complejidad en la ciudad convencional.
La discusión sobre la aplicación de indicadores de sostenibilidad en un ámbito urbano particular, por su intensa vinculación a la actividad turística, permitirá establecer una caracterización en cuanto a la complejidad que existe en espacios funcionales relacionados con el ocio. Estos resultados, en general, facilitan la toma de decisiones en cuanto a la planificación de usos turísticos y la promoción del destino en beneficio de una mejora importante de la experiencia turística.
Inferring the type of activities in neighborhoods of urban centers may be helpful in a number of contexts including urban planning, content delivery and activity recommendations for mobile web users or may even yield to a deeper understanding of the geographical evolution of social life in the city . During the past few years, the analysis of mobile phone usage patterns, or of social media with longitudinal attributes, have aided the automatic characterization of the dynamics of the urban environment. In this work, we combine a dataset sourced from a telecommunication provider in Spain with a database of millions of geotagged venues from Foursquare and we formulate the problem of urban activity inference in a supervised learning framework. In particular, we exploit user communication patterns observed at the base station level in order to predict the activity of Foursquare users who checkin-in at nearby venues. First, we mine a set of machine learning features that allow us to encode the input telecommunication signal of a tower. Subsequently, we evaluate a diverse set of supervised learning algorithms using labels extracted from Foursquare place categories and we consider two application scenarios. Initially, we assess how hard it is to predict specific urban activity of an area, showing that Nightlife and Entertainment spots are those easier to infer, whereas College and Shopping areas are those featuring the lowest accuracy rates. Then, considering a candidate set of activity types in a geographic area, we aim to elect the most prominent one. We demonstrate how the difficulty of the problem increases with the number of classes incorporated in the prediction task, yet the classifiers achieve a considerably better performance compared to a random guess even when the set of candidate classes increases.
Desde la aparición de Internet el mundo está cambiando de forma espectacular haciéndose más social, local y móvil (SoLoMo). La generalización de dispositivos móviles ha hecho que podamos geolocalizarnos en cualquier sitio y compartir la información a tiempo real con nuestras redes sociales.
La geolocalización cobra una nueva dimensión y aparecen nuevos conceptos: los mapas en Internet, la geolocalización social, el geomarketing y el geocommerce, la geolocalización aumentada, el geoposicionamiento web, el geoposicionamiento emocional y la geolocalización personal.
Gersón Beltrán, geógrafo profesional, reúne algunos de los artículos publicados en su blog en torno a la Geolocalización y las Redes Sociales para que se entienda este nuevo escenario, acompañado de anexos enlazando videos de sus ponencias, presentaciones de decenas de conferencias y cursos, así como referencias a documentos de gran interés.
Reassembling the Social is a fundamental challenge from one of the world's leading social theorists to how we understand society and the 'social'. Bruno Latour's contention is that the word 'social', as used by Social Scientists, has become laden with assumptions to the point where it has become misnomer. When the adjective is applied to a phenomenon, it is used to indicate a stablilized state of affairs, a bundle of ties that in due course may be used to account for another phenomenon. But Latour also finds the word used as if it described a type of material, in a comparable way to an adjective such as 'wooden' or 'steely'. Rather than simply indicating what is already assembled together, it is now used in a way that makes assumptions about the nature of what is assembled. It has become a word that designates two distinct things: a process of assembling; and a type of material, distinct from others. Latour shows why 'the social' cannot be thought of as a kind of material or domain, and disputes attempts to provide a 'social explanations' of other states of affairs. While these attempts have been productive (and probably necessary) in the past, the very success of the social sciences mean that they are largely no longer so. At the present stage it is no longer possible to inspect the precise constituents entering the social domain. Latour returns to the original meaning of 'the social' to redefine the notion, and allow it to trace connections again. It will then be possible to resume the traditional goal of the social sciences, but using more refined tools. Drawing on his extensive work examining the 'assemblages' of nature, Latour finds it necessary to scrutinize thoroughly the exact content of what is assembled under the umbrella of Society. This approach, a 'sociology of associations', has become known as Actor-Network-Theory, and this book is an essential introduction both for those seeking to understand Actor-Network Theory, or the ideas of one of its most influential proponents.
In investigating the mutual and dynamic relationship between urban development and consumption, this book asks: how are cities moulded by consumption, and how is consumption moulded by cities? Consumption stands at the intersection of different spheres of everyday life: between the public and the private, the political and the personal, the individual and the social. It is considered to be a means and motor of social change; as an active ingredient in the construction of space and place, and in constructing subjectivity and social selfhood. Providing a critical review of the ways in which urban development has been conceptualized, this book critiques urban regeneration initiatives, examines ordinary and spectacular consumption, and describes the relationship between consumption and development of the modern and post-modern city. It investigates: consumption and the city consumption and everyday life consumption, cities and identity consumption and urban regeneration. Consumption is understood to have multiple roles as a political, economic and cultural touchstone, and to be an active ingredient in the construction of place and space. Using international case studies and illustrations throughout, this book thoroughly analyzes consumption and the city, and provides a useful text for students of urban studies, sociology and geography.
El auge de las redes sociales como lugar de encuentro virtual ha traído consigo nuevas formas de interacción ciudadana. Éstas, a su vez, han trascendido a una escala espacio-temporal tal que su estudio resulta difícilmente abarcable por métodos tradicionales. A partir de las relaciones que acontecen en línea, las redes sociales recogen una gran cantidad de datos que se actualizan en tiempo real. Así, el objetivo de esta investigación se basa en utilizar estos datos, a modo de
muestra representativa, para identificar las preferencias sociales en relación a los espacios de las ciudades turísticas. Se plantea como estudio de caso la ciudad de Benidorm por ser ésta la ciudad turística por excelencia de la provincia de Alicante, con una importante proyección internacional. La metodología consta de tres fases: primero, una aplicación informática obtiene datos de las redes sociales: Foursquare y Twitter; a continuación, los datos son clasificados para que, por último, sean georreferenciados y grafiados en una cartografía para visualizar y evaluar los resultados. Una vez
representada la información es posible determinar, por un lado, qué ámbitos de la ciudad de Benidorm adquieren relevancia por ser lugares de concurrencia ciudadana y a partir de los cuales se establece comunicación e intercambio social; y, por otro lado, dar lectura al carácter turístico de la ciudad identificando el tipo y género al que pertenecen sus lugares de interés. La utilización de estas herramientas posibilita la interpretación de los flujos sociales que se producen en el espacio urbano y secunda el planteamiento de estrategias de planificación y gestión, particularmente en el ámbito turístico.
The penetration and use of social media services differs from city to city. This paper is aimed to provide a comparison of the use of Twitter between different cities of the world. We present a temporal analysis of activity on Twitter in 15 cities. Our study consists of two parts: First, we created temporal graphs of the activity in the 15 cities, through which hours of high and low activity could be identified. Second, we created heat map visualizations of the Twitter activities during the period of 19 September 2012–25 September 2013. The heat map visualizations make the periods of intense and sparse activity apparent and provide a snapshot of the activity during the whole year.
We describe Visone, a tool that facilitates the visual exploration of social networks. Social network analysis is a methodological approach in the social sciences using graph-theoretic concepts to describe, understand and explain social structure. The Visone software is an attempt to integrate analysis and visualization of social networks and is intended to be used in research and teaching. While we are primarily focusing on users in the social sciences, several features provided in the tool will be useful in other fields as well.