RT Book
T1 Modelling Regional Crime Risk using Directed Graph of Check-ins
A1 Rumi, Shakila Khan
A2 Salim, Flora D.
LA English
YR 2020
UL https://krimdok.uni-tuebingen.de/Record/186615267X
AB 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.Comment: 4 Pages, This paper has been accepted to publish in Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM' 20