Evert, Stefan
Proisl, Thomas
Jannidis, Fotis
Pielström, Steffen
Schöch, Christof
Vitt, Thorsten
2015-05-01
<p>Burrows’s Delta is the most established measure for stylometric difference in literary authorship attribution. Several improvements on the original Delta have been proposed. However, a recent empirical study showed that none of the proposed variants constitute a major improvement in terms of authorship attribution performance. With this paper, we try to improve our understanding of how and why these text distance measures work for authorship attribution. We evaluate the effects of standardization and vector normalization on the statistical distributions of features and the resulting text clustering quality. Furthermore, we explore supervised selection of discriminant words as a procedure for further improving authorship attribution.</p>
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https://doi.org/10.5281/zenodo.18177
oai:zenodo.org:18177
Zenodo
isbn:978-1-941643-36-5
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Proceedings of the Fourth Workshop on Computational Linguistics for Literature (at NAACL HLT 2015), Denver, Colorado, USA, June 4, 2015
stylometry
distance measures
standardization
normalization
authorship attribution
German literature
French literature
British literature
Towards a better understanding of Burrows’s Delta in literary authorship attribution
info:eu-repo/semantics/conferencePaper