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Journal ArticleDOI

‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship

John Burrows
- 01 Sep 2002 - 
- Vol. 17, Iss: 3, pp 267-287
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TLDR
A new way of using the relative frequencies of the very common words for comparing written texts and testing their likely authorship, which offers a simple but comparatively accurate addition to current methods of distinguishing the most likely author of texts exceeding about 1,500 words in length.
Abstract
This paper is a companion to my 'Questions of authorship: attribution and beyond', in which I sketched a new way of using the relative frequencies of the very common words for comparing written texts and testing their likely authorship. The main emphasis of that paper was not on the new procedure but on the broader consequences of our increasing sophistication in making such comparisons and the increasing (although never absolute) reliability of our inferences about authorship. My present objects, accordingly, are to give a more complete account of the procedure itself; to report the outcome of an extensive set of trials; and to consider the strengths and limitations of the new procedure. The procedure offers a simple but comparatively accurate addition to our current methods of distinguishing the most likely author of texts exceeding about 1,500 words in length. It is of even greater value as a method of reducing the field of likely candidates for texts of as little as 100 words in length. Not unexpectedly, it works least well with texts of a genre uncharacteristic of their author and, in one case, with texts far separated in time across a long literary career. Its possible use for other classificatory tasks has not yet been investigated.

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Citations
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Journal IssueDOI

A survey of modern authorship attribution methods

TL;DR: A survey of recent advances of the automated approaches to attributing authorship is presented, examining their characteristics for both text representation and text classification.
Book

Authorship Attribution

TL;DR: This review shows that the authorship attribution discipline is quite successful, even in difficult cases involving small documents in unfamiliar and less studied languages; it further analyzes the types of analysis and features used and tries to determine characteristics of well-performing systems, finally formulating these in a set of recommendations for best practices.
Journal IssueDOI

Computational methods in authorship attribution

TL;DR: Three scenarios are considered here for which solutions to the basic attribution problem are inadequate; it is shown how machine learning methods can be adapted to handle the special challenges of that variant.
Proceedings Article

Authorship attribution

TL;DR: In this paper, the authors explore information retrieval methods such as tf-Idf structure with support vector machines, parametric and nonparametric methods with supervised and unsupervised classification techniques in authorship attribution.
References
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Journal ArticleDOI

Feature-Finding for Text Classification

TL;DR: Results of a benchmark test on ten representative text-classification problems suggest that the technique here designated Monte-Carlo Feature-Finding has certain advantages that deserve consideration by future workers in this area.
Journal ArticleDOI

The application of principal component analysis to stylometry

TL;DR: In recent years principal component analysis has become popular for investigations in computational stylistics, particularly for studies of authorship, but the mathematical nature of the theory that underpins the method makes it rather inaccessible to linguists and literary scholars.
Journal ArticleDOI

A widow and her soldier: Stylometry and the American Civil war

TL;DR: This investigation strongly suggests that Pickett's widow, LaSalle Corbell Pickett, did compose the published letters, and they have been questioned, at least in part, by writers and historians of the Civil War.
Journal ArticleDOI

The Provenance of De Doctrina Christiana, attributed to John Milton: A Statistical Investigation

TL;DR: In this paper, a stylometric analysis of De Doctrina Christiana, a theological treatise attributed to John Milton, was performed, and the authors found that frequently occurring words are effective authorial discriminators between the treatise and the control texts.