Using alliteration in authorship attribution of historical texts

Abstract

The paper describes the use of alliteration, by itself or in combination with other features, in training machine learning algorithms to perform attribution of texts of unknown/disputed authorship. The methodology is applied to a corpus of 18th century political writings, and used to improve the attribution accuracy.