Uncovering patterns of ties among regions within metropolitan areas using data from mobile phones and online mass media.

Given the abundant quantities of big spatiotemporal geographic data that are available, interactions among spatial entities can now be extracted from various perspectives. This research investigates the spatial interactions within the metropolis of Beijing quantitatively. Two methods of quantifying the interactions are proposed. These interactions can be calculated from either individual trajectories extracted from mobile phone records or the co-occurrence of the toponyms of administrative units mentioned in online news items. By fitting these two types of data with a gravity model and comparing the results, we determine that the distance decay effect exists in both data sets, and this effect is more obvious in the interactions computed from the human trajectories. The spatial interactions and connections quantified from the two data sources display greater numbers of mutual patterns in the central urban areas, whereas more diversity is observed in the suburban areas. We conclude that the choice of assumptions as to which data can adequately represent spatial interactions significantly affects the results; therefore, rigorous examination of specific problems is needed to redefine the problems in a more specific way. [ABSTRACT FROM AUTHOR]