Table Of ContentHugh Craig and Brett Greatley-Hirsch extend the computational analysis GC
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introduced in Shakespeare, Computers, and the Mystery of Authorship ea
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(edited by Hugh Craig and Arthur F. Kinney; Cambridge, 2009) beyond tg ,
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problems of authorship attribution to address broader issues of literary yn
history. Using new methods to answer long-standing questions and -Hd
and Early Modern
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challenge traditional assumptions about the underlying patterns and r
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contrasts in the plays of Shakespeare and his contemporaries, the authors
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shed light on, for example, different linguistic usages between plays written
in verse and prose, company styles and different character types. As a shift
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Cr from a canonical survey to a corpus-based literary history founded on a a t Beyond Authorship
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ig an statistical analysis of language, this book represents a fundamentally new ly le
d G approach to the study of English Renaissance literature and proposes a new M , C Hugh Craig and
rea model and rationale for future computational scholarship in early modern o o
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ley literary studies. d m Brett Greatley-Hirsch
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ch Hugh Craig is Professor of English at the University of Newcastle, n t
. 97 Australia. D er
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1 Brett Greatley-Hirsch is University Academic Fellow in Textual Studies
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01 and Digital Editing at the University of Leeds. a d
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. J
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. C ‘This is an outstanding book of major importance... As well as conveying
M new knowledge of exceptional interest, it is written in a style that makes it
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comprehensible by a wide, non-specialist readership. I anticipate that it will
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generate intense interest, not least because it debunks a series of current
myths about authorship and the style of drama in Shakespeare’s time, and
introduces new methods of literary criticism.’
Gabriel Egan, Director, Centre for Textual Studies, De Montfort University
Printed in the United Kingdom Cover illustration: The Librarian, Giuseppe
Arcimboldo (c1566). Oil on canvas. Skoklosters
Castle collection (SKO 11616).
STYLE, COMPUTERS, AND
EARLY MODERN DRAMA
BeyondAuthorship
Hugh Craig and Brett Greatley-Hirsch extend the computational
analysis introduced in Shakespeare, Computers, and the Mystery of
Authorship(editedbyHughCraigandArthurF.Kinney;Cambridge
University Press, 2009) beyond problems of authorship attribution
to address broader issues of literary history. Using new methods to
answerlong-standingquestionsandchallengetraditionalassumptions
about the underlying patterns and contrasts in the plays of Shake-
speare and his contemporaries, Style, Computers, and Early Modern
Dramashedslighton,forexample,differentlinguisticusagesbetween
playswritteninverseandprose,companystyles,anddifferentcharac-
tertypes.Asashiftfromacanonicalsurveytoacorpus-basedliterary
historyfoundedonastatisticalanalysisoflanguage,thisbookrepre-
sentsafundamentallynewapproachtothestudyofEnglishRenais-
sance literature and proposes a new model and rationale for future
computationalscholarshipinearlymodernliterarystudies.
hugh craig, University of Newcastle, Australia, has published on
authorship attribution problems, mainly in Shakespeare, and on
widerstylisticquestions.Hehasongoingcollaborationsinbioinfor-
maticsandspeechpathology,resultinginarticlesinsomeleadingsci-
encejournals.HeisontheAuthorshipAttributionBoardforTheNew
OxfordShakespeareandisaFellowoftheAustralianAcademyofthe
Humanities.
brett greatley-hirschisUniversityAcademicFellowinTextual
Studies and Digital Editing at the University of Leeds. He is Coor-
dinating Editor of Digital Renaissance Editions and co-editor of
Shakespeare,thejournaloftheBritishShakespeareAssociation.Before
moving to the United Kingdom, he served as Vice President of the
AustralianandNewZealandShakespeareAssociation.
STYLE, COMPUTERS, AND
EARLY MODERN DRAMA
Beyond Authorship
HUGH CRAIG
UniversityofNewcastle,Australia
BRETT GREATLEY-HIRSCH
UniversityofLeeds
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education,learningandresearchatthehighestinternationallevelsofexcellence.
www.cambridge.org
Informationonthistitle:www.cambridge.org/9781107191013
doi:10.1017/9781108120456
C HughCraigandBrettGreatley-Hirsch2017
⃝
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithoutthewritten
permissionofCambridgeUniversityPress.
Firstpublished2017
PrintedintheUnitedKingdombyClays,StIvesplc
AcataloguerecordforthispublicationisavailablefromtheBritishLibrary
isbn978-1-107-19101-3Hardback
CambridgeUniversityPresshasnoresponsibilityforthepersistenceoraccuracy
ofurlsforexternalorthird-partyinternetwebsitesreferredtointhispublication,
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ForJohnBurrows,whomade
commonwordsuncommon
Contents
ListofFigures pageviii
ListofTables xiv
Acknowledgements xvi
NoteonTexts xviii
Introduction 1
1Methods 29
2ProseandVerse:Sometimes‘transparent’,SometimesMeeting
with‘ajolt’ 53
3SistersundertheSkin:CharacterandStyle 79
4 StageProperties:Bed,Blood,andBeyond 110
5 ‘Noveltycarriesitaway’:CulturalDrift 136
6Authorship,CompanyStyle,and horrorvacui 164
7 RestorationPlaysand‘theGiantRace,beforetheFlood’ 202
Coda 224
AppendixA:Play-TextsintheFullCorpus 227
AppendixB:Characterswith!2,000WordsofDialoguefrom243
PlaysPerformedontheCommercialStage,1580–1642 240
AppendixC:PlaysFirstAppearingontheCommercialStage
1590–1609,withTotalsforProp-TypesandLinesSpoken 247
AppendixD:Distributionof691Prop-Typesacross160PlaysFirst
AppearingontheCommercialStage,1590–1609 255
AppendixE:AListof221FunctionWords 261
WorksCited 262
Index 278
vii
Figures
1.1 PCAscatterplotof2,000-wordnon-overlappingsegmentsof
playslistedinTable1.1,usingthe500mostfrequent
words. page33
1.2 PCAscatterplotof2,000-wordnon-overlappingsegmentsof
playslistedinTable1.1,labelledbygenre,usingthe500most
frequentwords. 36
1.3 PCAbiplotof2,000-wordnon-overlappingsegmentsof
playslistedinTable1.1,labelledbygenre,usingthe500most
frequentwords. 37
1.4 PCAbiplotof2,000-wordnon-overlappingsegmentsof
playslistedinTable1.1,labelledbygenre,usingthe500most
frequentwordsandhighlightingpersonalpronouns. 38
1.5 Binarydecisiontreediagram. 40
1.6 Diagramofasinglebinarydecisiontreepopulatedfor
RandomForestsclassificationof2,000-word
non-overlappingsegmentsinatrainingdatasetof109
segmentsdrawnfromplayslistedinTable1.1,usingthe500
mostfrequentwords. 43
1.7 DeltadistancesbetweenGalateaandfourauthorialsub-sets. 46
1.8 DeltadistancesforTheJewofMaltaandfourauthorial
sub-sets. 47
2.1 PCAscatterplotofproseandversepartsfor7Shakespearean
charactersusingthe100mostfrequentfunctionwords. 60
2.2 PCAbiplotofproseandversesamplesfrom7Shakespearean
characters,usingthe100mostfrequentfunctionwords,
highlightingthe48mostweightedword-variables. 61
2.3 Columnchartofword-variablesexceedingthe0.01
probabilitythresholdinthegroupsplaysdetailed
inTables2.2–2.4. 69
viii
Figures ix
2.4 Columnchartofword-variablesexceedingthe0.01
probabilitythresholdinthegroupsplaysdetailedin
Tables 2.2–2.5. 72
2.5 Columnchartofword-variablesexceedingthe0.01
probabilitythresholdinthegroupsofplaysdetailedin
Tables2.2and2.5. 73
3.1 Distancesbetweencharactersinplaysandtheirsequels,using
percentagecountsofthe100mostcommonfunctionwords
combinedbySquaredEuclideanDistance. 82
3.2 Histogramofdistancesbetween666charactersbasedon
percentagecountsofthe100mostcommonfunctionwords
(221,445pairingsintotal). 83
3.3 Thez-scoresforthe20mostcommonfunctionwordsfor
OrgilusandIthoclesinJohnFord’sTheBrokenHeart,using
averagesandstandarddeviationsfromthefullsetof666
characterswith!2,000wordsofdialogue. 85
3.4 Distancesforthetenclosestmatchesfortencharacterswith
veryclosepairingswithanothercharacter. 87
3.5 The10closestpairingsforthe11characterswithdialogues
!8,000words,orderedbythedistancetotheirclosest
match. 89
3.6 Thez-scoresforthe20mostcommonfunctionwordsfor
Fluellen(HenrytheFifth),usingaveragesandstandard
deviationsfromthefullsetof666characterswith!2,000
wordsofdialogue. 91
3.7 Thez-scoresforthetenclosestmatchesfortencharacters
withverydistantclosestmatches,orderedbydistancetothe
closestmatch. 93
3.8 Totalwordsspoken,numberofandcombinedtotalwords
spokenbycharacterswith!2,000wordsofdialogue
in11playsperformedin1599byprofessionalcompanies. 96
3.9 Thez-scoresforthe20mostcommonfunctionwordsfor
BrutusandCassiusinShakespeare’sJuliusCaesar,using
averagesandstandarddeviationsfromthesetof666
characterswith!2,000wordsofdialogue. 97
3.10 Hierarchicalclusteranalysisof35characterparts,using
Ward’sLinkageandSquaredEuclideanDistance,basedon
countsofthe100mostcommonfunctionwords. 99
