Mining e-mail content for author identification forensics

We describe an investigation into e-mail content mining for author identifi cation, or authorship attribution, for the purpose of forensic investigatio n. We focus our discussion on the ability to discriminate between authors f or the case of both aggregated e-mail topics as well as across different em ail topics. An extended set of e-mail document features including structura l characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by diffe rent authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation.