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Page 1: 1/26 Corpus Linguistics. 2/26 Varieties of English Relevance of corpus linguistics to this course –Previously studies of stylistics were largely informal

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Corpus Linguistics

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Varieties of English

• Relevance of corpus linguistics to this course– Previously studies of stylistics were largely

informal and subjective– Using computers to look at larger amounts of

data allows us to be more formal and objective– “Corpus linguistics” basically provides a

“mindset” (and some procedures) for doing this

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What is a corpus?

• Corpus (pl. corpora) = ‘body’• Collection of written text or transcribed speech • Usually but not necessarily purposefully collected• Usually but not necessarily structured• Usually but not necessarily annotated• (Usually stored on and accessible via computer)• Corpus ~ text archive

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“Purposefully collected”

• Text samples collected to meet a specific need

• Corpus may be quite focused, eg corpus of newswire texts, or may be more general

• Issue of balance often important– Demographic features (age, sex, location, social

class of writer/reader)– Different styles and genres

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“Structured”

• Overall corpus is divided into sections defined by parameters

• Again balance will ensure that different genres or demographic features are equally represented

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Parameters in the BNC (written portion)

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Genre distinctions in the BNC (written portion)

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Parameters in BNC (spoken part)

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Parameters in BNC (spoken part) cont

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“Annotated”• Not just plain text• Most corpora are at least “POS tagged”

– Each word has its part of speech (POS) identified– POS tags contain quite rich information, eg not just

“verb” but including some morphological information

– tags also disambiguate, eg between book (N/V) if possible

• Some may also have other information indicated– structural information resulting from parse– word sense distinctions for same-POS homonyms

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What is corpus linguistics?

• Not a branch of linguistics, like socio~, psycho~, …

• Not a theory of linguistics

• A set of tools and methods (and a philosophy) to support linguistic investigation across all branches of the subject

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Evidence in linguistics

• Real attested usage as linguistic evidence• Contrasts with introspective approach previously

typical• Relates to the competence~performance

(langue~parole) distinction• Corpus linguists often more interested in trends

than rules (probabilities rather than certainties)• Famous stories of corpus evidence contradicting

widely-held assumptions about language use.

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Activities in corpus linguistics

• Design and compilation of corpora• Development of tools for corpus analysis• Descriptive linguists using corpora to

analyze lexical and grammatical behaviour of language, eg for lexicography, and of course stylistics

• Exploiting corpora in applied linguistics – language teaching, translation.

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History of Corpus Linguisticswww.essex.ac.uk/linguistics/clmt/w3c/corpus_ling/content/history.html

• Textual study has always included an element of counting and cataloguing, despite impracticalities – notably concordances of Shakespeare, the Bible, etc.

• Arrival of computers in 1950s of course changed everything

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Brown corpus

• First modern computer-readable corpus• W.N. Francis and H. Kučera, Brown

University, Providence, RI • one million words of American English

texts printed in 1961 • sampled from 15 different text categories • used as model for other corpora, including

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LOB corpus

• compiled by researchers in Lancaster, Oslo and Bergen

• one million words of British English texts printed in 1961

• sampled from same 15 text categories as Brown corpus

• All texts ≤ 2,000 words long• Kolhapur corpus of Indian English compiled in

1978 to same sepcification

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The London-Lund Corpus of Spoken English (LLC)

• First corpus of transcribed spoken language• Part of Survey of Spoken English at Lund

University under the direction of J. Svartvik• 500,000 words of spoken British English

recorded from 1953 to 1987 • different categories, such as spontaneous

conversation, spontaneous commentary, spontaneous and prepared oration

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COBUILD

• 1m-word corpus too small for many applications• 1980: Collins instigated collection of 20m-word

corpus to support lexicographers writing new Collins Birmingham University International Learners’ Dictionary (John Sinclair)

• Now expanded to Bank of English corpus, 320m words and growing

• www.collins.co.uk/Corpus/CorpusSearch.aspx• www.collins.co.uk/books.aspx?group=153

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BNC (1995)

• http://www.natcorp.ox.ac.uk/• 100m word collection of written and spoken text

from 1975-93 (already dated in some respects!)• Carefully designed and balanced• Corpus is closed (finite, synchronic)• All text tagged to high quality• Lots of tools available for exploration• Nice online interface (available on campus)

http://bnc.humanities.manchester.ac.uk/cgi-bnc/BNCquery.pl?theQuery=search&urlTest=yes

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What can you do with a corpus?

• Many things, but just some examples:

• Investigate behaviour of words and how they relate to genre, mode, sex of speaker/hearer

• Prove (or disprove) supposed trends with quantitative data

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Example 1: swearing

• Women and men swear (and use taboo words) differently

• Data (from BNC spoken part) shows– Women and men use different swear words– They use them for different effect (men use them to

disparage, women use them to intensify)– Their use changes depending on the sex of the

listener(s): women swear more in single-sex groups; men don’t swear more in mixed-sex than amongst themselves

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Example 2.1: Near synonyms

• Subtle differences in the meaning of near synonyms can be distinguished by looking at the words they collocate with– “You shall know a word by the company it

keeps” (Firth)

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frail vs fragile

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Example 2.2: Near synonyms• In addition, near synonyms can be shown to be

favoured depending on genre, eg big vs large

Category big large

 Spoken conversation 768.55 488.34

 Other spoken material 395.89 447.58

 Newspapers 365.27 431.62

 Fiction and verse 333 293.06

 Other published written material 290.84 223.43

 Unpublished written material 247.39 186.35

 Non-academic prose and biography 139.63 181.19

 Academic prose 38.85 45.11

Frequency per million words