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Literary and Linguistic Computing Advance Access originally published online on June 17, 2005
Literary and Linguistic Computing 2005 20(Suppl 1):59-67; doi:10.1093/llc/fqi024
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© The Author 2005. Published by Oxford University Press on behalf of ALLC and ACH. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A Controlled-corpus Experiment in Authorship Identification by Cross-entropy

Patrick Juola

Duquesne University, USA

R. Harald Baayen

University of Nijmegen, The Netherlands

Correspondence: Patrick Juola, Department of Mathematics and Computer Science, Duquesne University, Pittsburgh, PA 15282, USA. E-mail: juola{at}mathcs.duq.edu
This article describes an authorship, and more generally document classification, experiment on a pre-existing Dutch corpus of university writings. By measuring linguistic distances using a cross-entropy technique, a technique sensitive not only to the distributions of language features, but also to their relative intersequencing, classification judgments can be made with great sensitivity, significance, confidence, and accuracy. In particular, despite the designed difficulty of the Dutch corpus used, the technique was still able to reliably detect not only authorship, but also subtle features of register, topic, and even the educational attainments of the author. We present evidence suggesting that this technique outperforms more well-known techniques such as function word principle components analysis or linear discriminant analysis, as well as suggest ways in which performance can be improved.


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