Week 12 - Personal

January 8, 2018 | Author: Anonymous | Category: Arts & Humanities, Writing, Spelling
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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 Ratio Number 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



Gaga Corpus



I you the and it



I you the oh me

   

I = 5.09% me = 1.3%

   

1 = 4.4% me = 2.03%

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



Gaga Corpus



Ranked 7 1.3%



Ranked 9 1.59%





Top 5 content words 

100 Song Corpus



Gaga Corpus



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



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



Gaga Corpus



‘m and can Know ‘ll



‘m want ‘ll don’t can

   

Span: 1L, 1R

   

Top 5 collocates of ‘love 

100 Song Corpus



Gaga Corpus



I you my me the



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

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