Authors: Christopher Galbraith (Department of Statistics, University of California, Irvine), Padhraic Smyth (Department of Computer Science, University of California, Irvine), and Hal S. Stern (Department of Statistics, University of California, Irvine)



A common question in forensic analysis is whether two observed data sets originated from the same source or from different sources. Statistical approaches to addressing this question have been widely adopted within the forensics community, particularly for DNA evidence. Here we investigate the application of statistical approaches to same-source forensic questions for spatial event data, such as determining the likelihood that two sets of observed GPS locations were generated by the same individual. We develop two approaches to quantify the strength of evidence in this setting. The first is a likelihood ratio approach based on modeling the spatial event data directly. The second approach is to instead measure the similarity of the two observed data sets via a score function and then assess the strength of the observed score resulting in the score-based likelihood ratio. A comparative evaluation using geolocated Twitter event data from two large metropolitan areas shows the potential efficacy of such techniques.