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Corpus analysis (1)

Corpus analysis (1). Corpus Linguistics Richard Xiao lancsxiaoz@googlemail.com. 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?.

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Corpus analysis (1)

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  1. Corpus analysis (1) Corpus Linguistics Richard Xiao lancsxiaoz@googlemail.com

  2. Outline of the session • Lecture • Concordance • Patterning • Semantic prosody • Wordlist • Cluster (lexical bundle, MWU, n-gram) • Lab • WST Concord and Wordlist • AntConc • Online concordancers

  3. 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…

  4. 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 nodeword, is in a central position with all lines vertically aligned around the node • Can be sorted to reveal patterns of usage

  5. Concordancer • A concordancer is the software that displays concordances • Concord WordSmith Tools (GBP50) • www.lexically.net/wordsmith/ • MonoConc (USD85) • www.athel.com/mono.html • AntConc (free) • www.antlab.sci.waseda.ac.jp/software/antconc3.2.1w.exe • Xaira (free) • www.oucs.ox.ac.uk/rts/xaira/ • Multilingual Corpus Tool (MLCT) - free • www.lancs.ac.uk/fass/projects/corpus/cbls/resources.asp

  6. KWIC concordance (WST)

  7. KWIC concordance (MonoConc)

  8. KWIC concordance (AntConc)

  9. KWIC concordance (Xaira)

  10. Online concordancers • English (free) • http://corpus.byu.edu/bnc/ • http://bncweb.lancs.ac.uk/bncwebSignup/user/login.php • http://www.americancorpus.org/ • Chinese (free) • http://score.crpp.nie.edu.sg/laohong/lcmc.htm • http://score.crpp.nie.edu.sg/laohong/UCLA.htm • http://score.crpp.nie.edu.sg/laohong/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/

  11. Syntagmatic vs. paradigmatic

  12. Collocation is syntagmatic Langue (Language system) paradigmatic famous boots. Onthe stroke offull time the Stoke the lead onthe stroke ofhalf-time with a goal Smith sin-binned onthe stroke ofhalf-time, added a clinched their win onthe stroke oflunch after resuming chase by declaring onthe stroke oflunch. <p> With a lead expectant crowd, onthe stroke ofmidday. The bird hour began not uponthe stroke ofmidnight but upon the of midnight but uponthe stroke ofnoon. There was, booked in advance. Onthe stroke ofseven, a gong summons Promptly onthe stroke ofsix 'clock, the chooks from Edinburgh onthe stroke ofthe Millennium. Parole (Utterance)syntagmatic

  13. Example of pattern meaning • “on the stroke of X” • X = a temporal point • “It is/was adj. that…” • 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.

  14. 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 thatstrontium 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)

  15. 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

  16. 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)

  17. 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

  18. 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…

  19. 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

  20. Semantic prosody • PROVIDE: a positive semantic prosody • facilities, information, services; aid, assistance, help, support; care, food, money, nourishment, protection, security • CREATE: “prosodically mixed or incomplete” • [Negative] illusion, problems • [Neutral] atmosphere, conditions, environment, image, impression, situation, space • [Positive] jobs, opportunities, order, wealth

  21. Semantic prosody • The negative (or less frequently positive) prosody that belongs to an 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 is 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 used with 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)

  22. 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

  23. Semantic prosody • Semantic prosody is strongly collocational in that it operates beyond the meanings of individual words • Both personaland priceare quite neutral, but when they co-occur, a negative prosody may result: personal pricemost 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 negative

  24. “Personal price” typically negative and high something undesirable Barclays’ slogan to promote their personal financial services The personal loan with the personal price

  25. 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

  26. 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)

  27. 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

  28. 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 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 • Standard 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 falls • In order to remedy the issue of comparing TTRs of corpora of different sizes, WordSmith can calculate TTR based on every 1,000 words and produce an average TTR

  29. Wordlist

  30. AntConc wordlist

  31. Practice • Make a wordlist of the following text using wordlist function in WST or AntConc • The Stephen text (local copy avialable) • http://www.cch.kcl.ac.uk/legacy/teaching/av1000/textanalysis/gaskin/stephen.txt • Browse through the frequency list. Can you see any pattern in the list?

  32. 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 recurring/specific expressions for a corpus • Tools • WordSmith • Concord • Wordlist (Index) • AntConc • N-gram

  33. Cluster/lexical bundle/n-gram Concord (3-gram) Wordlist

  34. 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?

  35. Clusters in WordSmith • Make adjustments here

  36. Concord: “know”

  37. 3-word clusters of “know” recompute n-word clusters

  38. Clusters in Wordlist (Index)

  39. Clusters in Wordlist (Index) The index is created and saved in the specified file location Warning: Your file location may be different!

  40. Resulting index

  41. Clusters in Wordlist (Index) • OR: Wordlist – File – Open

  42. Clusters in Wordlist (Index)

  43. Clusters in Wordlist (Index)

  44. N-gram in AntConc Can a word contain the apostrophe?

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