a sprinkling of key words

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A Sprinkling of Key Words Mike Scott Aston University June 30, 2010

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A Sprinkling of Key Words. Mike Scott Aston University June 30, 2010. Issues: Key words (KWs). Keyness Aboutness Distribution patterns of KWs. complex pattern. or simple. fractal?. Fractal. - PowerPoint PPT Presentation

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Page 1: A Sprinkling of Key Words

A Sprinkling of Key Words

Mike ScottAston UniversityJune 30, 2010

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Issues: Key words (KWs)

Keyness AboutnessDistribution patterns of KWs

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complex pattern

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or simple

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fractal?

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Fractal

• A fractal is "a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole,"[1] a property called self-similarity – (Wikipedia)– [1] Mandelbrot, B.B. (1982). The Fractal

Geometry of Nature. W.H. Freeman and Company.

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Keyness

• aboutness

• importance

• a textual category

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aboutness

• what the text is about

• what the message is

• what it all means

• picture from mindreadersdictionary.com

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importance

centrality

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Context

• Claimp by Maya Goldblum

• New Designers 07

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Impoverished context

• Dandelion Light by Sunghwa Jang

• New Designers 07

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Levels of Context

P hysica l env ironm ent

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Identification of KWs: criteria

simple verbatim repetitionno allowance for anaphora, synonymy, antonymy etc.thresholdone word, or more than one?

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Corpus-bound or corpus-driven?

• Machine-identified keyness is ideal for corpus-driven research

• The researcher lets the PC suggest areas needing further chasing up

• See recent work by McEnery, Baker, etc. and Nelia Scott 1998

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Research Questions

How are the KWs of Bleak House distributed? Are the KWs of different kinds (nouns/verbs … character/place/style words) distributed differently?Do the KWs of the chapters reflect the pattern of the whole text but on a smaller scale?

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Bleak House

published 1852-3(20 monthly instalments)

350,000 wordsPreface + 66 Chapters

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reference corpus

9 million words52 novels,

29 other 19th Century authors23 Dickens

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Procedures

• download Bleak House (Gutenberg Project)

• separate each chapter as a separate file

• create a wordlist of the reference corpus

• create a wordlist of the whole of Bleak House

• create a batch of wordlists, one of each chapter of Bleak House

ref. corpus

BH

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KW Procedures

• Compute KW list of the whole novel

• Compute batch of KW lists, one for each chapter

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Overall Results

Over 300 positive KWs for the whole novelAbout 70 negative KWs including God (half as frequent as in 19th C literature overall)

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Excel• spreadsheet constructed at

the same time as the batch of KW files

http:\\www.lexically.net\downloads\corpus_linguistics\Bleak_House.xls

fewer characters in first chapters

pronouns are sprinkled

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Chapter by Chapter

Average of 23 KWs per chapter – same settings, same reference corpus (19th C Lit.)Per chapter: minimum 5, maximum 38.

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Chapter by chapter variationKW Categories

0%

20%

40%

60%

80%

100%

120%

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67

Other

Characters

Places

Pronouns

Titles

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Global KWs

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Local KWs

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middling burstiness

• verbsappears

begins

puts

observes

replies

continues

says

considers

etc.

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Preliminary findings

• All chapters have KWs• Individual chapters differ considerably in their

KWs• because KWs are not all global• Character KWs enter the novel gradually• Pronouns and verbs present in many sections

but absent in many too– not much to do with aboutness– middling level of burstiness

• KWs of different kinds are distributed differently

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Preliminary conclusion

• KWs of the chapters do not simply reflect the pattern of the whole text but on a smaller scale

• Keyness is not fractal

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References• Baker, P., Gabrielatos C., Khosravinik, M., Krzyzanowski, M.,

McEnery, T. & Wodak, R., 2008. A useful methodological synergy? Combining critical discourse analysis and corpus linguistics to examine discourses of refugees and asylum seekers in the UK press. Discourse & Society 19(3), 273-305.

• McEnery, Tony, 2009. "Keywords and Moral Panics: Mary Whitehouse and Media Censorship". in Dawn Archer (ed.) What's in a Word-list? Investigating word frequency and keyword extraction. Farnham: Ashgate, 93-124.

• Scott, M. Nelia, 1998, Normalisation and Readers' Expectations: A Study of Literary Translation with Reference to Lispector's A Hora da Estrela. Liverpool: Unpublished PhD thesis, University of Liverpool.