In this paper we present a model for email authorship identification (EAI) by employing a Cluster-based Classification (CCM) technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature-set to include some more interesting and effective features for email authorship identification (e.g. the last punctuatio...

With the popularity of Internet technologies and applications, inappropriate or illegal online messages have become a problem for the society. The goal of authorship attribution for anonymous online messages is to identify the authorship from a group of potential suspects for investigation identification. Most previous contributions focused on extracting various writing-style features and emplo...

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