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Appl Netw Sci. 2016;1(1):12. doi: 10.1007/s41109-016-0014-z. Epub 2016 Nov 16.

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

Author information

1
1Department of Computer Science, University of Alicante, Ap. Correos 99, Alicante, E-03080 Spain.
2
2Department of Urbanism, University of Alicante, Ap. Correos 99, Alicante, E-03080 Spain.
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Contributed equally

Abstract

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.

KEYWORDS:

Data visualization; Foursquare; Network analysis; Street network; Twitter

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