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Corpus analysis (1) Corpus Linguistics Richard Xiao
Outline of the session Lecture –Concordance –Patterning –Semantic prosody –Wordlist –Cluster (lexical bundle, MWU, n-gram) Lab –WST Concord and Wordlist –AntConc –Online concordancers
Who reads a corpus? A corpus is usually too large for anyone to read, e.g. the BNC is very, very large… –It took 4 years to build –It contains over 100 million (100,106,008) words of modern English –It comprises 4,124 texts –There are six and a quarter million sentence units in the whole corpus –Each word is automatically assigned a part of speech code - there are 65 parts of speech identified –It occupies 1.5 gigabytes of disk space - the equivalent of more than 1,000 high capacity floppy disks –The whole corpus printed in small type on thin paper would take up 10 metres of shelf space –Reading the whole corpus aloud at a rate of 150 words a minute, eight hours a day, 365 days a year, would take nearly 4 years A computer can scan in a few seconds more text than you can read in your whole life…
Concordance A comprehensive index of the words used in a text or a corpus A set of concordance lines The most common concordance format is the KWIC concordance - Key Word in Context –In a KWIC concordance of your search word, i.e. the node word, is in a central position with all lines vertically aligned around the node Can be sorted to reveal patterns of usage
Concordancer A concordancer is the software that displays concordances (Unicode compliant) –Concord WordSmith Tools (GBP50) –MonoConc (USD85) –AntConc (free) –Xaira (free) –Multilingual Corpus Tool (MLCT) - free
KWIC concordance (WST)
KWIC concordance (MonoConc)
KWIC concordance (AntConc)
KWIC concordance (Xaira)
Online concordancers English (free) –http://corpus.byu.edu/bnc/http://corpus.byu.edu/bnc/ –http://bncweb.lancs.ac.uk/bncwebSignup/user/login.phphttp://bncweb.lancs.ac.uk/bncwebSignup/user/login.php –http://www.americancorpus.org/ (COCA)http://www.americancorpus.org/ Chinese (free) –www.lancs.ac.uk/fass/projects/corpus/LCMC/www.lancs.ac.uk/fass/projects/corpus/LCMC/ –www.lancs.ac.uk/fass/projects/corpus/UCLA/www.lancs.ac.uk/fass/projects/corpus/UCLA/ –www.lancs.ac.uk/fass/projects/corpus/babel/babel.htmwww.lancs.ac.uk/fass/projects/corpus/babel/babel.htm Sketch Engine: Corpus query system of multilingual data, incorporating word sketches, grammatical relations, and a distributional thesaurus (30 days free trial) –http://www.sketchengine.co.uk/http://www.sketchengine.co.uk/
Syntagmatic vs. paradigmatic
Collocation is syntagmatic famous boots. On the stroke of full time the Stoke the lead on the stroke of half-time with a goal Smith sin-binned on the stroke of half-time, added a clinched their win on the stroke of lunch after resuming chase by declaring on the stroke of lunch. With a lead expectant crowd, on the stroke of midday. The bird hour began not upon the stroke of midnight but upon the of midnight but upon the stroke of noon. There was, booked in advance. On the stroke of seven, a gong summons Promptly on the stroke of six 'clock, the chooks from Edinburgh on the stroke of the Millennium. Parole (Utterance) syntagmatic Langue (Language system) paradigmatic
Example of pattern meaning on the stroke of X –X = a temporal point It is/was adj. that… (construction grammar?) –certain, likely, possible, probable, etc. –apparent, clear, evident, obvious, plain, etc. –fantastic, marvellous, appropriate, logical, encouraging, exciting, reassuring, etc. –appalling, unjust, annoying, etc. –critical, important, necessary, vital, etc. –amazing, funny, interesting, intriguing, etc.
Pattern meaning A large number of different adjectives occur in the pattern between is/was and that –Probability It was important to establish this because it was possible that strontium and calcium in fossils might have reacted chemically with the rock in which the fossils were buried. (New Scientist) –Evaluation - used to evaluate propositions (statements) rather than things or people But a lot of health authorities say they will not allow these drugs on NHS prescription as they cannot afford them at around £90 a month. It is scandalous that the rich can buy the drugs privately, but tough luck if you are poor. (The Sun)
Meaning arising from collocation There are always semantic relations between node and collocates, and among the collocates themselves. (Stubbs 2002: 225) –Collocational meaning arising from the semantic relations between node and collocates: semantic prosody (also called discourse prosody) –Collocational meaning arising from the semantic relations among collocates of a node: semantic preference
What is semantic prosody? consistent aura of meaning with which a form is imbued by its collocates (Louw 1993: 157) a form of meaning which is established through the proximity of a consistent series of collocates. (Louw 2000: 57) the spreading of connotational colouring beyond single word boundaries (Partington 1998: 68) When the usage of a word gives an impression of an attitudinal or pragmatic meaning, this is called a semantic prosody (Sinclair 1999) This kind of meaning is prosody in the sense that it stretches over more than one unit (word)
Semantic prosody The primary function of SP is to express speaker/writer attitude or evaluation (Louw 2000: 58) –Attitudinal, affective, evaluative and pragmatic meaning Typically negative, with relatively few of them bearing an affectively positive meaning –Unsurprising: contented human beings utter much less than discontented ones –It is unrequited love, not requited love, that forms most of the subject matter for the greatest love poetry in English!
Semantic prosody SET IN: occurs primarily with subjects which refer to unpleasant states of affairs –…before bad weather sets in… –…the fact that misery can set in… –…desperation can set in… –…stagnation seemed to have set in… –…before rigor mortis sets in… BREAK OUT: it is bad things that break out –…violence broke out… –…riots broke out… –…war broke out… –…real disagreements have broken out… –…a storm of protest broke out…
Semantic prosody Collocates of CAUSE –damage, problems, pain, disease, distress, trouble, concern, degradation, harm, pollution, suffering, anxiety, death, fear, stress, symptoms –These examples of bad company collocate with cause so frequently that the central and typical use of cause shows a negative affective meaning ( ) Collocates of consequences –In the sense of result serious, disastrous, adverse, dire, damaging, negative, unintended, unfortunate, tragic, fatal, severe –In the sense of importance important, significant, far-reaching, profound
Semantic prosody The negative (or less frequently positive) prosody that belongs to an lexical item is the result of the interplay between the item and its typical collocates –The item does not appear to have an affective meaning until it appears in the context of its typical collocates –If a word has typical collocates with an affective meaning, it may take on that affective meaning even when it is used with other atypical collocates The consequence of a word frequently keeping bad company is that the use of the word alone may become enough to indicate something unfavourable (cf. Partington 1998: 67)
Semantic prosody Is semantic prosody a type of connotative meaning? Semantic prosodies are not merely connotational as the force behind semantic prosodies is more strongly collocational than the schematic aspects of connotation. (Louw 2000: 49-50) In my view, connotation can be collocational or non-collocational; semantic prosody can only be collocational
Semantic prosody Semantic prosody is strongly collocational in that it operates beyond the meanings of individual words Both personal and price are quite neutral, but when they co-occur, a negative prosody may result: personal price most frequently refers to something undesirable –In the BoE with over 550 million words of written and spoken texts, 20 instances of personal price are all evaluatively negative
Personal price Barclays slogan to promote their personal financial services in 2003 The personal loan with the personal price typically negative and high something undesirable
Semantic preference a lexical set of frequently occurring collocates [sharing] some semantic feature (Stubbs 2002: 449) –large typically collocates with items from the same semantic set indicating quantities and sizes number(s), scale, part, quantities, amount(s) –absence/change of state is a common feature of the collocates of maximizers such as utterly, totally, completely and entirely
Semantic preference Semantic preference and semantic prosody are two distinct yet interdependent collocational meanings –Semantic prosody is a further level of abstraction of the relationship between lexical units (Sinclair 1996, 1998; Stubbs 2001) Collocation (the relationship between a node and individual words) Colligation (the relationship between a node and grammatical categories, e.g. very tends to collocate with adjectives and adverbs) Semantic preference (semantic sets/fields of collocates) Semantic prosody (affective meanings of a given node with its typical collocates)
Semantic preference Semantic preference and semantic prosody have different operating scopes (Partington 2004:151) –Semantic preference can be viewed as a feature of the collocates while semantic prosody is a feature of the node word The two also interact (Partington 2004: 151) –Semantic prosody dictates the general environment which constrains the preferential choices of the node item –Semantic preference contributes powerfully to building semantic prosody End of concordance versus patterning, collocation and colloational meaning
Wordlist A list of words in a corpus and their frequency –Can become very meaningful when compared with other lists: keyword analysis A type is not a token. –Token: an occurrence of any given word form (6 tokens) –Type: a (unique) word form (5 types - a is repeated) Type-token ratio (TTR): the number of types divided by the number of tokens multiplies 100 –lexical density: a low TTR indicates a text is not very lexically rich –useful when comparing samples of roughly equal length Standardized type-token ratio (STTR) –It is difficult to compare the TTR of a smaller corpus against a larger one As a corpus gets bigger, the number of new word types being counted declines –In order to remedy the issue of comparing TTRs of corpora of different sizes, WordSmith can calculate TTR based on every 1,000 words (the default setting can be adjusted) and produce an average TTR
Practice Make a wordlist of the following text using wordlist function in WST or AntConc –The Stephen text (local copy available) xtanalysis/gaskin/stephen.txthttp://www.cch.kcl.ac.uk/legacy/teaching/av1000/te xtanalysis/gaskin/stephen.txt A book written by the hippie guru Stephen Gaskell Browse through the frequency list. Can you see any pattern in the list?
Cluster Also called lexical bundle, n-gram, multi-word unit (MWU) Groups of N words which appear in sequence in the text Presented using frequency lists Good way to identify recurrent/specific expressions for a corpus Tools –WordSmith Concord Wordlist (Index) –AntConc N-gram
Clusters in WordSmith The Stephen text Clusters with WST Concord –The search term Clusters with WST Wordlist (Index) –The whole corpus Questions –What are the most frequent 3-word clusters with know in the Stephen text? – What are the most frequent 3-word clusters in the whole text? Are they all expected phrases?
Clusters in WordSmith Make adjustments here
3-word clusters of know recompute n-word clusters
Clusters in Wordlist (Index) An error may occur if you specify a folder without having the writing permissions
Clusters in Wordlist (Index) The index is created and saved in the specified file location Warning: Your file location may be different!
Clusters in Wordlist (Index) OR: Wordlist – File – Open
Clusters in Wordlist (Index)
N-gram in AntConc Difference from WST: Can a word contain the apostrophe?