  The location-based social network, Foursquare, reflects the human activities
of a city. The mobility dynamics inferred from Foursquare helps us
understanding urban social events like crime In this paper, we propose a
directed graph from the aggregated movement between regions using Foursquare
data. We derive region risk factor from the movement direction, quantity and
crime history in different periods of the day. Later, we propose a new set of
features, DIrected graph Flow FEatuRes (DIFFER) which are associated with
region risk factor. The reliable correlations between DIFFER and crime count
are observed. We verify the effectiveness of the DIFFER in monthly crime count
using Linear, XGBoost, and Random Forest regression in two cities, Chicago and
New York City.
