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On the importance of temporal dynamics in modeling urban activity

The vast amount of available spatio-temporal data of human activities and mobility has given raise to the rapidly emerging field of urban computing/informatics. Central to the latter is understanding the dynamics of the activities that take place in an urban area (e.g., a city). This can significantly enhance functionalities such as resource and service allocation within a city. Existing literature has paid a lot of attention on spatial dynamics, with the temporal ones often being neglected and left out. However, this can lead to non-negligible implications. For instance, while two areas can appear to exhibit similar activity when the latter is aggregated in time, they can be significantly different when introducing the temporal dimension. Furthermore, even when considering a specific area X alone, the transitions of the activity that takes place within X are important themselves. Using data from the most prevalent location-based social network (LBSN for short), Foursquare, we analyze the temporal dynamics of activities in New York City and San Francisco. Our results clearly show that considering the temporal dimension provides us with a different and more detailed description of urban dynamics. We envision this study to lead to more careful and detailed consideration of the temporal dynamics when analyzing urban activities.