  We present a method to capture groupings of similar calls and determine their
relative spatial distribution from a collection of crime record narratives. We
first obtain a topic distribution for each narrative, and then propose a
nearest neighbors relative density estimation (kNN-RDE) approach to obtain
spatial relative densities per topic. Experiments over a large corpus
($n=475,019$) of narrative documents from the Atlanta Police Department
demonstrate the viability of our method in capturing geographic hot-spot trends
which call dispatchers do not initially pick up on and which go unnoticed due
to conflation with elevated event density in general.
