Conference Proceedings

Gender-preferential text mining of e-mail discourse

M Corney, O De Vel, A Anderson, G Mohay

Proceedings - Annual Computer Security Applications Conference, ACSAC | Published : 2002

Abstract

This paper describes an investigation of authorship gender attribution mining from e-mail text documents. We used an extended set of predominantly topic content-free e-mail document features such as style markers, structural characteristics and gender-preferential language features together with a support vector machine learning algorithm. Experiments using a corpus of e-mail documents generated by a large number of authors of both genders gave promising results for author gender categorisation.

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