Authorship identification in large email collections: Experiments using features that belong to different linguistic levels Notebook for PAN at CLEF 2011
George K. Mikros, Kostas Perifanos · 2011
The aim of this paper is to explore the usefulness of using features from different linguistic levels to email authorship identification. Using various email datasets provided by PAN'11 lab we tested several feature groups in both authorship attribution and authorship verification subtasks. The selected feature groups combined with Regularized Logistic Regression and One-Class SVM ma- chine learning methods performed well above average in authorship attribution subtasks and below average in authorship verification subtasks.