Estimating the Amenability of New Domains for Deception Detection

摘要

In this paper we present an initial experiment in the estimation of the amenability of new domains to true/false classification. We choose four domains, two of which have been classified for deception, and use the out-of-rank distance measure on n-grams to aid in deciding whether the third and fourth domains are amenable to T/F classification. We then use a classifier covered in the literature to train on the verified domains and test on the new domains to determine whether the relative distance measure can be a predictor of classification accuracy.