Analysing successful public spaces in an urban street network using data from the social networks Foursquare and Twitter-Reference-Cited by-同舟云学术

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

Published:2016-11-16 Issue:1 Volume:1 Page:
ISSN:2364-8228
Container-title:Applied Network Science
language:en
Short-container-title:Appl Netw Sci

Author:

Agryzkov Taras,Martí Pablo,Nolasco-Cirugeda Almudena,Serrano-Estrada Leticia,Tortosa Leandro,Vicent José F.

Funder

Ministerio de Economía y Competitividad

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computer Networks and Communications,Multidisciplinary

Link

http://link.springer.com/content/pdf/10.1007/s41109-016-0014-z.pdf

Reference21 articles.

1. Adnan, M, Leak A, Longley P (2014) A geocomputational analysis of Twitter activity around different world cities. Geo-spatial Inform Sci 17(3): 145–152.

2. Agryzkov, T, Oliver JL, Tortosa L, Vicent JF (2012) An algorithm for ranking the nodes of an urban network based on concept of PageRank vector. Appl Math Comput 219: 2186–2193.

3. Berkhin, P (2005) A survey on PageRank computing. Internet Math 2(1): 73–120.

4. Casalania, V, Rittel H (1967) Generating Floor Plans from Adjacency Matrices. MIT, Cambridge.

5. Crucitti, P, Latora V, Porta S (2006a) The network analysis of urban streets: a primal approach. Environ Plann B 33(5): 705–725.

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