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Mining the Social Media Data for a Bottom-Up Evaluation of Walkability

In: Traffic and Granular Flow '17

Author

Listed:
  • Christian Berzi

    (University of Milano-Bicocca, CSAI-Complex Systems and Artificial Intelligence Research Centre, Department of Informatics, Systems and Communications)

  • Andrea Gorrini

    (University of Milano-Bicocca, CSAI-Complex Systems and Artificial Intelligence Research Centre, Department of Informatics, Systems and Communications)

  • Giuseppe Vizzari

    (University of Milano-Bicocca, CSAI-Complex Systems and Artificial Intelligence Research Centre, Department of Informatics, Systems and Communications)

Abstract

Urbanization represents a huge opportunity for computer applications enabling cities to be managed more efficiently while, at the same time, improving the life quality of their citizens. One of the potential applications of this kind of systems is a bottom-up evaluation of the level of walkability of the city (namely, the level of usefulness, comfort, safety and attractiveness of an urban area for walking). This is based on the usage of data from social media for the computation of structured indicators describing the actual usage of areas by pedestrians. This paper will present an experimentation of analysis of data about the city of Milano (Italy) acquired from Flickr and Foursquare. Over 500 thousand points, which represent the photos and the POIs collected from the above-mentioned social media, were clustered through an iterative approach based on the DBSCAN algorithm, in order to achieve homogeneous areas defined by the actual activity of inhabitants and tourists rather than by a top-down administrative procedure and to supply useful indications on the level of walkability of the city of Milan.

Suggested Citation

  • Christian Berzi & Andrea Gorrini & Giuseppe Vizzari, 2019. "Mining the Social Media Data for a Bottom-Up Evaluation of Walkability," Springer Books, in: Samer H. Hamdar (ed.), Traffic and Granular Flow '17, pages 167-175, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-11440-4_20
    DOI: 10.1007/978-3-030-11440-4_20
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