Using Corpus Tools in Discourse Analysis

Discourse and Pragmatics

Week 12

What is a corpus? An collection of a large number of texts of a

particular type in digital format which can be easily searched and manipulated with computer programs

What is corpus linguistics ? The analaysis of collections of texts (corpora)

with computer tools in order to detect grammatical, lexical or discourse level patterns, often with the aim of comparing those patterns with those found in other collections of texts.

Examples of corpus assisted discourse analysis Flowerdew (1997, 2002)

Anlaysis of the speeches of Gov. Chris Patten and CE Tung Chee Hwa

common themes: free market economy, freedom of the individual, rule of law

Divergent themes: democracy, stability and harmony

Rey (2001) Startrek characters from 1966 to 1993 Female language has shifted from being more

relational to more informational Male language has shifted from being more

informational to more relational

Advantages of using corpora Easily detecting grammatical and lexical

patterns in a large number of texts Reducing researcher bias Efficiently detecting differences among

varieties, registers, genres, and Discourses

Corpus based (deductive) vs. Corpus driven (inductive) analysis

Disadvantages of using corpora Separation of discourse from its social context Corpus data usually confined to text (cannot

account for images, non-verbal behavior and other aspects of multimodal discourse)

Frequency does not equal importance (sometimes very important messages are implicit or ‘taken for granted’ rather than explicit)

‘People don’t say what they mean and people don’t mean what they say’

Words have multiple meanings and word meanings change over time and according to the context in which they are used

Tools for corpus analysis Online corpora and concordancers

Collins Bank of English British National Corpus Corpus of Contemporary American English International Corpus of English

General vs. Specialized Corpora

Software tools AntConc ConcApp WordSmith Tools

Preparing corpora Collecting data (Internet? Scanning files?) Txt files Separate files for different texts ‘Cleaning’ files ‘Tagging’

Procedures in corpus analysis Type token ratio Dispersion plots Frequency lists Concordance data Collocation calculations Keyword calculations

Example Lady Gaga’s lyrics Total of 59 songs Reference corpus: 100 top songs from

November 2010

Type Token RatioNumber of types divided by the number of tokens

Type Token Ratio Low indicates narrow range of subjects, lack of

variety or frequent repetition High indicates wide range of subjects, great

variation, less frequent repetition BNC Written = 45.53 BNC Spoken = 32.96 Baker’s Holiday Pamphlets = 40.03 100 Song Corpus = 9.07 Gaga Corpus = 11.4

Frequency lists

Frequency Function words (articles, prepositions,

conjunctions, pronouns, etc.) Useful in answering questions about style, register Pronouns can be particularly important

Content words (nouns, verbs, adjectives, adverbs) Useful in answering questions about topics/

Discourses

Top 5 function words 100 Song Corpus

I you the and it

Gaga Corpus

I you the oh me

1 = 4.4%me = 2.03%

I = 5.09%me = 1.3%

Murphey 1992: The word count revealed that the total referents in first person (I, me, my, mine, etc.) amounted to 10% of the total words

‘t (not) 100 Song Corpus

Ranked 7 1.3%

Gaga Corpus

Ranked 9 1.59%

Top 5 content words 100 Song Corpus

like no can baby know (love) (0.42%)

Gaga Corpus

love (0.98%) baby can want know

Concordances

Concordances Can reveal contexts of frequent words Sorting strategies Searching for patterns

Concordances

Collocation ‘Co-location’ The frequency with which words appear close

to other words ‘You shall know a lot about a word from the

company it keeps.’ (Firth 1957) Span (xL, xR)

Top 5 collocates for ‘I’ 100 Song Corpus

‘m and can Know ‘ll

Gaga Corpus

‘m want ‘ll don’t can

Span: 1L, 1R

Top 5 collocates of ‘love 100 Song Corpus

I you my me the

Gaga Corpus

I fu want ‘t revenge

Span 5l, 5R

Keywords The frequency of words in a corpus in relation

to another corpus The statistical significance of a keyword's

frequency in a given corpus, relative to a reference corpus.

Keywords

Keywords: semantic domains lover* romance* love* loves

fame* fancy* ribbons* glitter fashion vanity rich presents famous

retro* bang* shake* dirty* grease* bad* teeth monster filthy

oh* eh*

What does this analysis tell us out Lady Gaga lyrics? Style and texture Whos doing whats Discourses and ideology