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An Examination of Personal Mobility Patterns in Space and Time Using Twitter

Author

Listed:
  • Mark Birkin

    (School of Geography, University of Leeds, Leeds, UK)

  • Kirk Harland

    (School of Geography, University of Leeds, Leeds, UK)

  • Nicolas Malleson

    (School of Geography, University of Leeds, Leeds, UK)

  • Philip Cross

    (School of Geography, University of Leeds, Leeds, UK)

  • Martin Clarke

    (School of Geography, University of Leeds, Leeds, UK)

Abstract

New sources of data relating to personal mobility and activity patterns are now providing a unique opportunity to explore movement patterns at increasing scales of spatial and temporal refinement. In this article, a corpus of messages from the Twitter social networking platform are examined. An elementary classification of users is proposed on the basis of frequency of use in space and time. The behaviour of different user groups is investigated across small areas in the major conurbation of Leeds. Substantial variations can be detected in the configuration of individual networks. An interpretation of the patterns which result is provided in terms of the underlying demographic structures, and the basic form and function of the urban area.

Suggested Citation

  • Mark Birkin & Kirk Harland & Nicolas Malleson & Philip Cross & Martin Clarke, 2014. "An Examination of Personal Mobility Patterns in Space and Time Using Twitter," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 5(3), pages 55-72, July.
    • Handle: RePEc:igg:jaeis0:v:5:y:2014:i:3:p:55-72
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    Cited by:

    1. Annetta Burger & Talha Oz & William G. Kennedy & Andrew T. Crooks, 2019. "Computational Social Science of Disasters: Opportunities and Challenges," Future Internet, MDPI, vol. 11(5), pages 1-31, April.

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