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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