How where is when? On the regional variability and resolution of geosocial temporal signatures for points of interest

The temporal characteristics of human behavior with respect to points of interest (POI) differ significantly with place type. Intuitively, we are more likely to visit a restaurant during typical lunch and dinner times than at midnight. Aggregating geosocial check-ins of millions of users to the place type level leads to powerful temporal bands and signatures. In previous work these signatures have been used to estimate the place being visited based purely on the check-in time, to label uncategorized places based on their individual signature's similarity to a type signature, and to mine POI categories and their hierarchical structure from the bottom up. However, not all hours of the day and days of the week are equally indicative of the place type, i.e., the information gain between temporal bands that jointly form a place type signature differs. To give a concrete example, places can be more easily categorized into weekend and weekday places than into Monday and Tuesday places. Nonetheless, research on the regional variability of temporal signatures is lacking. Intuitively, one would assume that certain types of places are more prone to regional differences with respect to the temporal check-in behavior than others. This variability will impact the predictive power of the signatures and reduce the number of POI types that can be distinguished. In this work, we address the regional variability hypothesis by trying to prove that all place types are created equal with respect to their temporal signatures, i.e., temporal check-in behavior does not change across space. We reject this hypothesis by comparing the inter-signature similarity of 321 place types in three major cities in the USA (Los Angeles, New York, and Chicago). Next, we identify a common core of least varying place types and compare it against signatures extracted from the city of Shanghai, China for cross-culture comparison. Finally, we discuss the impact of our findings on POI categorization and the reliability of temporal signatures for check-in behavior in general.