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Sensitivity of location-sharing services data: evidence from American travel pattern


  • Zhenhua Chen


  • Laurie Schintler


This paper investigates sensitivity of location-sharing services (LSS) data with a focus on understanding American daily travel pattern using three LSS datasets: Brightkite, Gowalla and Foursquare. Through a systematic data refining process, person miles of travel and daily person trip are created and compared both among themselves and with the US National Household Travel Survey (NHTS) of 2009. The results suggest that LSS data provides a better estimation of person miles of travel than daily person trip on average. In addition, the comparison with the NHTS reveals that LSS data tends to have a better reflection of daily travel behavior among metro areas with high population density. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Zhenhua Chen & Laurie Schintler, 2015. "Sensitivity of location-sharing services data: evidence from American travel pattern," Transportation, Springer, vol. 42(4), pages 669-682, July.
  • Handle: RePEc:kap:transp:v:42:y:2015:i:4:p:669-682
    DOI: 10.1007/s11116-015-9596-z

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    References listed on IDEAS

    1. Laurie A Schintler & Rajendra Kulkarni & Kingsley Haynes & Roger Stough, 2014. "Sensing ‘socio-spatio’ interaction and accessibility from location-sharing services data," Chapters, in: Ana Condeço-Melhorado & Aura Reggiani & Javier Gutiérrez (ed.),Accessibility and Spatial Interaction, chapter 5, pages 92-110, Edward Elgar Publishing.
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    Cited by:

    1. Schintler, Laurie A. & Fischer, Manfred M., 2018. "Big Data and Regional Science: Opportunities, Challenges, and Directions for Future Research," Working Papers in Regional Science 2018/02, WU Vienna University of Economics and Business.


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