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Using Shakespeare's Sotto Voce to Determine True Identity From Text
Little is known of the private life of William Shakespeare, but he is famous for his collection of plays and poems, even though many of the works attributed to him were published anonymously. Determining the identity of Shakespeare has fascinated scholars for 400 years, and four significant figures...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862847/ https://www.ncbi.nlm.nih.gov/pubmed/29599734 http://dx.doi.org/10.3389/fpsyg.2018.00289 |
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author | Kernot, David Bossomaier, Terry Bradbury, Roger |
author_facet | Kernot, David Bossomaier, Terry Bradbury, Roger |
author_sort | Kernot, David |
collection | PubMed |
description | Little is known of the private life of William Shakespeare, but he is famous for his collection of plays and poems, even though many of the works attributed to him were published anonymously. Determining the identity of Shakespeare has fascinated scholars for 400 years, and four significant figures in English literary history have been suggested as likely alternatives to Shakespeare for some disputed works: Bacon, de Vere, Stanley, and Marlowe. A myriad of computational and statistical tools and techniques have been used to determine the true authorship of his works. Many of these techniques rely on basic statistical correlations, word counts, collocated word groups, or keyword density, but no one method has been decided on. We suggest that an alternative technique that uses word semantics to draw on personality can provide an accurate profile of a person. To test this claim, we analyse the works of Shakespeare, Christopher Marlowe, and Elizabeth Cary. We use Word Accumulation Curves, Hierarchical Clustering overlays, Principal Component Analysis, and Linear Discriminant Analysis techniques in combination with RPAS, a multi-faceted text analysis approach that draws on a writer's personality, or self to identify subtle characteristics within a person's writing style. Here we find that RPAS can separate the known authored works of Shakespeare from Marlowe and Cary. Further, it separates their contested works, works suspected of being written by others. While few authorship identification techniques identify self from the way a person writes, we demonstrate that these stylistic characteristics are as applicable 400 years ago as they are today and have the potential to be used within cyberspace for law enforcement purposes. |
format | Online Article Text |
id | pubmed-5862847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58628472018-03-29 Using Shakespeare's Sotto Voce to Determine True Identity From Text Kernot, David Bossomaier, Terry Bradbury, Roger Front Psychol Psychology Little is known of the private life of William Shakespeare, but he is famous for his collection of plays and poems, even though many of the works attributed to him were published anonymously. Determining the identity of Shakespeare has fascinated scholars for 400 years, and four significant figures in English literary history have been suggested as likely alternatives to Shakespeare for some disputed works: Bacon, de Vere, Stanley, and Marlowe. A myriad of computational and statistical tools and techniques have been used to determine the true authorship of his works. Many of these techniques rely on basic statistical correlations, word counts, collocated word groups, or keyword density, but no one method has been decided on. We suggest that an alternative technique that uses word semantics to draw on personality can provide an accurate profile of a person. To test this claim, we analyse the works of Shakespeare, Christopher Marlowe, and Elizabeth Cary. We use Word Accumulation Curves, Hierarchical Clustering overlays, Principal Component Analysis, and Linear Discriminant Analysis techniques in combination with RPAS, a multi-faceted text analysis approach that draws on a writer's personality, or self to identify subtle characteristics within a person's writing style. Here we find that RPAS can separate the known authored works of Shakespeare from Marlowe and Cary. Further, it separates their contested works, works suspected of being written by others. While few authorship identification techniques identify self from the way a person writes, we demonstrate that these stylistic characteristics are as applicable 400 years ago as they are today and have the potential to be used within cyberspace for law enforcement purposes. Frontiers Media S.A. 2018-03-15 /pmc/articles/PMC5862847/ /pubmed/29599734 http://dx.doi.org/10.3389/fpsyg.2018.00289 Text en Copyright © 2018 Kernot, Bossomaier and Bradbury. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Kernot, David Bossomaier, Terry Bradbury, Roger Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title | Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title_full | Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title_fullStr | Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title_full_unstemmed | Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title_short | Using Shakespeare's Sotto Voce to Determine True Identity From Text |
title_sort | using shakespeare's sotto voce to determine true identity from text |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862847/ https://www.ncbi.nlm.nih.gov/pubmed/29599734 http://dx.doi.org/10.3389/fpsyg.2018.00289 |
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