“Mingled Yarn”: The State of Computing in Shakespeare 2.0

Hirsch, Brett D.; Craig, Hugh

doi:10.4324/9781315264226-1

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…Inside DH, "Drametrics" is a sub-research field, specialized on quantitative analysis of the literary genre of drama (Romanska, 2015). Digital Shakespeare research and projects have gotten attention since the 2000s (Hirsch, 2014;Mueller, 2008). The dramatic structures in the form of antagonisms are revealed by topic modeling algorithms, (Yavuz, 2019).…”

Section: Related Workmentioning

confidence: 99%

ItaGLAM: A corpus of Cultural Communication on Twitter during the Pandemic

Nolano¹,

Carlino²,

Buono³

et al. 2020

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

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Section: Related Workmentioning

confidence: 99%

ItaGLAM: A corpus of Cultural Communication on Twitter during the Pandemic

Nolano¹,

Carlino²,

Buono³

et al. 2020

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

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“…Jackson ( 2006 ) uses common low-frequency word phrases, repetition of phrases, collocation, and images to link word groups to other works. Vickers ( 2011 ) uses a tri-gram, or n-gram, approach, while (Hirsch and Craig, 2014 ) use function word frequency. They also use methods based on the Information Theoretic measure Jensen-Shannon divergence (JSD), and unsupervised graph partitioning clustering algorithms (Arefin et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Using Shakespeare's Sotto Voce to Determine True Identity From Text

2018

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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.

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Analyses of Character Networks in Dramatic Works by Using Graphs

Yavuz

2020

2020 7th International Conference on Behavioural and Social Computing (BESC)

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“Mingled Yarn”: The State of Computing in Shakespeare 2.0

Abstract: a s h g a t e. c o m a s h g a t e. c o m a s h g a t e. c o m a s h g a t e. c o m a s h g a t e. c o m a s h g a t e. c o m a s h g a t e .

Cited by 5 publications

References 5 publications

ItaGLAM: A corpus of Cultural Communication on Twitter during the Pandemic

ItaGLAM: A corpus of Cultural Communication on Twitter during the Pandemic

Using Shakespeare's Sotto Voce to Determine True Identity From Text

Analyses of Character Networks in Dramatic Works by Using Graphs

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