Attribution of 18th Century Political Writings Using Machine Learning

By Smiljana Petrovic, Gary Berton, Sean Campbell and Lubomir Ivanov.

Published by Journal of Technologies in Society

Format Price
Article: Print $US10.00
Published Online: October 14, 2015 $US5.00

Machine learning is used extensively in authorship attribution of both modern and historical writings. Our research concentrates on 18th century political writing, with a special focus on the work of Thomas Paine. Accurately determining authorship helps achieve a better understanding of the political, ideological, socio-economical and philosophical milieu of the period. This paper presents an enhancement of our prior authorship attribution methodology through the use of artificial neural networks in addition to the previously used support vector machines and centroids. We introduce a method that selects and combines base classifiers. This results in a significantly improved accuracy and confidence in the attribution results. The success of this project is also due to the close collaboration between computer scientists and historians. Automated text analysis brings the best-fitted author into the spotlight, to be cross-examined with historical facts and context. Our methodology has been applied to several 18th century articles. The attribution of two of those articles is also discussed in this paper.

Keywords: Authorship Attribution, Thomas Paine, Machine Learning

Journal of Technologies in Society, Volume 11, Issue 3, October 2015, pp.1-13. Article: Print (Spiral Bound). Published Online: October 14, 2015 (Article: Electronic (PDF File; 673.820KB)).

Dr. Smiljana Petrovic

Associate Professor, Computer Science Department, Iona College, New Rochelle, NY, USA

Gary Berton

Coordinator, Institute for Thomas Paine Studies, Iona College, New Rochelle, NY, USA

Sean Campbell

Student, Computer Science, Iona College, New Rochelle, NY, USA

Dr. Lubomir Ivanov

Associate Professor, Computer Science Department, Iona College, New Rochelle, NY, USA