Leticia Serrano-Estrada

Analysing successful public spaces in an urban street network using data from the social networks Foursquare and Twitter

This paper analyzes success public spaces (specifically plazas) in the urban fabric of the city of Murcia, Spain. Two approaches were adopted. Firstly, the city was visualized as a complex network whose nodes represent plazas. A centrality algorithm was applied to determine the importance of each node. Secondly, data sets were used from social networks Foursquare and Twitter, which provide different types of data as well as user profiles. Foursquare data indicates user preferences of urban public spaces, while in this respect Twitter offers less specific user generated data. Both perspectives have facilitated two rankings based on the most visited plazas in the city. The results enabled a comparative study to determine the potential differences or similarities between both approaches.

Morphological and functional attributes of preferred urban public spaces in Alicante province

Introduction Abstract. Understanding the role of urban public spaces in today’s historic Spanish Mediterranean cities is a key issue for researchers and urban professionals. Increasingly, social media showcases users’ preferences, a trend that can provide an indication as to why some urban public spaces are preferred over others. This research focuses on the study of morphological and functional attributes of preferred urban public spaces in historic cities of the Province of Alicante (Spain). Two main objectives are pursued: to describe urban morphological features of preferred plazas within the city; and, to identify functional patterns taking into account building uses and activities found in these public spaces. Eight plazas, selected from a previous study using Foursquare social media data, were used as a case study. The research

Studying Successful Public Plazas in the City of Murcia Spain Using a Ranking Nodes Algorithm and Foursquare Data

In this paper we study the success of public spaces exactly, plazas existing in the urban fabric of the city of Murcia, Spain, from two points of view. On the one hand, we apply an algorithm to classify the nodes of a graph in order of importance, from the data obtained through a fieldwork developed on the city itself. On the other hand, we use the data that gives us the social network Foursquare in this city to extract the preferences of its users, related to the different plazas present in the public space in the city. These two perspectives or views allows us to establish two rankings of plazas places in the city, which is the subject of comparative study to determine potential differences or similarities in the results.