Police departments in New York City may soon be using geo-tagged tweets to predict crime. It sounds like a far-fetched sci-fi scenario a la Minority Report, but when I contacted Dr. Matthew Greber, the University of Virginia researcher behind the technology, he explained that the system is far more mathematical than metaphysical. 

The system Greber has devised is an amalgam of both old and new techniques. Currently, many police departments target hot spots for criminal activity based on actual occurrences of crime. This approach, called kernel density estimation (KDE), involves pairing a historical crime record with a geographic location and using a probability function to calculate the possibility of future crimes occurring in that area. While KDE is a serviceable approach to anticipating crime, it pales in comparison to the dynamism of Twitter’s real-time data stream, according to Dr. Gerber’s research paper “Predicting Crime Using Twitter and Kernel Density Estimation”.