Measuring urban activities using Foursquare data and network analysis: a case study of Murcia (Spain)

International Journal of Geographical Information Science

Volumn 31, Issue 1, 2017, Pages 100-121

  Agryzkov, Taras ^a   Martí, Pablo ^a   Tortosa, Leandro ^a   Vicent, José F ^a  

^a UNIVERSITY OF ALICANTE   (Spain)

Author keywords

data visualization; PageRank algorithms; social networks analysis; street networks; Urban analysis

Indexed keywords

ALGORITHM; FIELDWORK; GIS; NETWORK ANALYSIS; SOCIAL NETWORK; URBAN AREA; VISUALIZATION;

MURCIA [MURCIA (ADS/PRV)]; MURCIA [SPAIN]; SPAIN;

EID: 84969850208     PISSN: 13658816     EISSN: 13623087     Source Type: Journal    
DOI: 10.1080/13658816.2016.1188931     Document Type: Article

References (30)

1. T.Agryzkov, et al., 2012. An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector. Applied Mathematics and Computation, 219, 2186–2193. doi:10.1016/j.amc.2012.08.064
2. T.Agryzkov, et al., 2014. Analyzing the commercial activities of a street network by ranking their nodes:a case study in Murcia, Spain. International Journal of Geographical Information Science, 28 (3), 479–495. doi:10.1080/13658816.2013.854370
3. M.Barthelemy, 2011. Spatial networks. Physics Reports, 499 (1–3), 1–101. doi:10.1016/j.physrep.2010.11.002
4. A.Bawa-Cavia, 2011. Sensing the urban:using location-based social network data in urban analysis. In:First workshop on pervasive urban applications (PURBA), 12–15 June, San Francisco, CA.
5. P.Berkhin, 2005. A survey on PageRank computing. Internet Mathematics, 2 (1), 73–120. doi:10.1080/15427951.2005.10129098
6. M.Bianchini, M.Gori, and F.Scarselli, 2005. Inside PageRank. ACM Transactions on Internet Technology, 5 (1), 92–128. doi:10.1145/1052934
7. P.Bonacich, 1987. Power and centrality:a family of measures. American Journal of Sociology, 92, 1170–1182. doi:10.1086/228631
8. U.Brandes, 2001. A faster algorithm for betweenness centrality. TheJournal of Mathematical Sociology, 25 (2), 163–177. doi:10.1080/0022250X.2001.9990249
9. D.Cerrone, 2015. A sense of place. Turku Urban Research Programmes. Research Report 1/2015. Available from:http://beta.turku.fi/sites/default/files/atoms/files/
10. P.Ciuccarelli, G.Lupi, and L.Simeone, 2014. Visualizing the data city. In:Social media as a source of knowledge for urban planning and management. Heidelberg:Springer.
11. J.Cranshaw, et al., 2012. The livehoods project:utilizing social media to understand the dynamics of a city. In:Proceedings of the 6th international AAAI conference on webblogs and social media, 4–7 June. Dublin:Trinity College.
12. P.Crucitti, V.Latora, and S.Porta, 2006a. The network analysis of urban streets:a dual approach. Physica A:Statistical Mechanics and its Applications, 369 (2), 853–866. doi:10.1016/j.physa.2005.12.063
13. P.Crucitti, V.Latora, and S.Porta, 2006b. Centrality measures in spatial networks of urban streets. Physical Review E, 73 (3), 036125. doi:10.1103/PhysRevE.73.036125
14. L.C.Freeman, 1977. A set of measures of centrality based on betweenness. Textitsociometry, 40 (1), 35–41.
15. N.E.Friedkin, 1991. Theoretical foundations for centrality measures. American Journal of Sociology, 96, 1478–1504. doi:10.1086/229694
16. I.Hong, 2015. Spatial analysis of location-based social networks in Seoul, Korea. Journal of Geographic Information System, 7, 259–265. doi:10.4236/jgis.2015.73020
17. S.K.Jeong, and Y.U.Ban, 2011. Computational algorithms to evaluate design solutions using Space Syntax. Computer-Aided Design, 43 (6), 664–676. doi:10.1016/j.cad.2011.02.011
18. L.Katz, 1953. A new status index derived from sociometric analysis. Psychometrika, 18, 39–43. doi:10.1007/BF02289026
19. D.Lazer, et al., 2009. Computational social science. Science, 323 (5915), 721–723. doi:10.1126/science.1167742
20. J.Lindqvist, et al., 2011. I’m the mayor of my house:examining why people use foursquare a social-driven location sharing application. In:Proceedings of the SIGCHI conference on human factors in computing systems HCI’11, 7–12 May, Vancouver, BC. New York:ACM, 2409–2418.
21. M.E.J.Newman, 2003. A measure of betweenness centrality based on random walks. Research Report. Available from:http://arXiv:cond-mat/0309045.
22. A.Noulas, C.Mascolo, and E.Frias-Martinez, 2013. Exploiting Foursquare and cellular data to infer user activity in urban environments. In:Proceedings of the IEEE 14th international conference on mobile data management, Milan. Washington, DC:IEEE Computer Society, 167–176.
23. A.Noulas, et al., 2011. An empirical study of geographic user activity patterns in foursquare. In:Proceedings of the fifth international AAAI conference on weblogs and social media, 17–21 July, Barcelona. Menlo Park, CA:The AAAI Press, 570–573.
24. D.Offenhuber, and C.Ratti, 2014. Decoding the city. In:Urbanism in the age of big data. Basel:Birkhäuser Verlag Gmbh.
25. L.Page, et al., 1999. The pagerank citation ranking:bringing order to the web. Technical report 1999-66. Stanford, CA:Stanford InfoLab.
26. S.Porta, P.Crucitti, and V.Latora, 2006. The network analysis of urban streets:a primal approach. Environment and Planning B:Planning and Design, 33, 705–725. doi:10.1068/b32045
27. O.Roick, and S.Heuser, 2013. Location based social networks – definition, current state of the art and research agenda. Transactions in GIS, 17, 763–784. doi:10.1111/tgis.12032
28. L.Serrano-Estrada, S.Serrano-Salazar, and F.Alvarez, 2014. Las redes sociales y los SIG como herramientas para conocer las preferencias sociales en las ciudades turísticas:el caso de Benidorm. In:XVI Congreso Nacional de Tecnologías de la Información Geográfica, Tecnologías de la información para nuevas formas de ver el territorio (in Spanish), 25–27 June, Alicante, 1005–1012.
29. T.H.Silva, et al., 2013. A comparison of foursquare and instagram to the study of city dynamics and urban social behavior. In:Proceedings of the 2nd ACM SIGKDD international workshop on urban computing, 11–14 August, Chicago, IL. New York:ACM.
30. K.Sohn, and D.Kim, 2010. Zonal centrality measures and the neighbourhood effect. Transportation Research Part A:Policy and Practice, 44 (9), 733–743.