‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship.
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| Title: | ‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship. |
|---|---|
| Authors: | Burrows, John1 john.burrows@netcentral.com.au |
| Source: | Literary & Linguistic Computing. Sep2002, Vol. 17 Issue 3, p267-287. 21p. 5 Charts. |
| Subjects: | Authorship, Authors, Literary characters, Literature, Statistics, Databases |
| 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. [ABSTRACT FROM PUBLISHER] |
| Copyright of Literary & Linguistic Computing is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 44626942 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: ‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Burrows%2C+John%22">Burrows, John</searchLink><relatesTo>1</relatesTo><i> john.burrows@netcentral.com.au</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Literary+%26+Linguistic+Computing%22">Literary & Linguistic Computing</searchLink>. Sep2002, Vol. 17 Issue 3, p267-287. 21p. 5 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Authorship%22">Authorship</searchLink><br /><searchLink fieldCode="DE" term="%22Authors%22">Authors</searchLink><br /><searchLink fieldCode="DE" term="%22Literary+characters%22">Literary characters</searchLink><br /><searchLink fieldCode="DE" term="%22Literature%22">Literature</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM PUBLISHER] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Literary & Linguistic Computing is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=44626942 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/llc/17.3.267 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 267 Subjects: – SubjectFull: Authorship Type: general – SubjectFull: Authors Type: general – SubjectFull: Literary characters Type: general – SubjectFull: Literature Type: general – SubjectFull: Statistics Type: general – SubjectFull: Databases Type: general Titles: – TitleFull: ‘Delta’: a Measure of Stylistic Difference and a Guide to Likely Authorship. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Burrows, John IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2002 Type: published Y: 2002 Identifiers: – Type: issn-print Value: 02681145 Numbering: – Type: volume Value: 17 – Type: issue Value: 3 Titles: – TitleFull: Literary & Linguistic Computing Type: main |
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