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

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Abstract

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.

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Notes

  1. It should be noted that the word “passive” only denotes the fact that these data is passively collected when the check-in is active by users. This is different from those devices and software that trace movements without any user interface, such as AirSage.

  2. “Check-ins” tend to be made at locations tied to recreational activities (see e.g., Cheng et al. 2011). However, the primary purpose of paper is to examine the extent to which “check-ins” can be used to proxy two indicators of travel behavior: daily person trips and personal miles traveled, and under what circumstances related to the size and density of metropolitan area “check-ins” are proxies. In doing so, we are also essentially quantifying the degree of error present in location-sharing services data. We appreciate one of the reviewer helped us to point the potential need to capture locations such as home and work, and to develop appropriate algorithms for accurately approximating these locations based on individual’s “check-in” patterns.

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Authors and Affiliations

  1. Sol Price School of Public Policy, University of Southern California, Los Angeles, USA

    Zhenhua Chen

  2. School of Policy, Government, and International Affairs, George Mason University, Fairfax, USA

    Laurie A. Schintler

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  1. Zhenhua Chen
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  2. Laurie A. Schintler
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Correspondence to Zhenhua Chen.

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Chen, Z., Schintler, L.A. Sensitivity of location-sharing services data: evidence from American travel pattern. Transportation 42, 669–682 (2015). https://doi.org/10.1007/s11116-015-9596-z

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