Author verification by linguistic profiling: An exploration of the parameter space

Abstract

This article explores the effects of parameter settings in linguistic profiling, a technique in which large numbers of counts of linguistic features are used as a text profile which can then be compared to average profiles for groups of texts. Although the technique proves to be quite effective for authorship verification, with the best overall parameter settings yielding an equal error rate of 3% on a test corpus of student essays, the optimal parameters vary greatly depending on author and evaluation criterion.