Exploring the textual positions and functions of lexical items in hard news stories

1. Exploring the textual positions and functions of lexical items in hard news stories Michael Hoey Matthew Brook O’Donnell Michaela Mahlberg Mike Scott 28th July - Corpus Linguistics 2007

2. Corpus linguistic context: There is a growing emphasis in corpus studies on extending lexical description beyond lexico-grammatical patterns

3. Corpus linguistic context: Corpus approach explores the link between form and meaning Most widely explored at level of concordance line Sinclair - Lexical Item Hunston & Francis - Pattern Grammar Stubbs - Discourse Prosody Hoey - Lexical Priming

4. Corpus linguistic context: Corpus approach explores the link between form and meaning • Most widely explored at level of concordance line • Sinclair - Lexical Item • Hunston & Francis - Pattern Grammar • Stubbs - Discourse Prosody • Hoey - Lexical Priming

5. The Lexical Priming claim All the features we notice prime us so that when we come to use the word ourselves, we are likely (in speech, particularly) to use it in the same lexical context, with the same grammar, in the same semantic context, as part of the same genre/style, in the same kind of social and physical context, with a similar pragmatics and in similar textual ways.

6. The Lexical Priming claim All the features we notice prime us so that when we come to use the word ourselves, we are likely (in speech, particularly) to use it in the same lexical context, with the same grammar, in the same semantic context, as part of the same genre/style, in the same kind of social and physical context, with a similar pragmatics and in similar textual ways.

7. Textual Priming • There are textual implications to this theory…

8. Textual Priming • There are textual implications to this theory… • namely that certain words and phrases have associations with the beginnings of texts and paragraphs

9. Textual Priming Project (AHRC): Aims • to investigate whether (and if so how many and what types of) lexical items are primed to appear in text-initial or paragraph-initial position to identify lexico-grammatical patterns and see how these patterns can be functionally interpreted in the textual contexts. to relate these lexical and corpus-driven facts to current textual descriptions of (hard) news stories that might provide explanations for the positive primings of relevant lexis. THANKS TO AHRC…

10. Textual Priming Project (AHRC): Aims • to investigate whether (and if so how many and what types of) lexical items are primed to appear in text-initial or paragraph-initial position • to identify lexico-grammatical patterns and see how these patterns can be functionally interpreted in the textual contexts. to relate these lexical and corpus-driven facts to current textual descriptions of (hard) news stories that might provide explanations for the positive primings of relevant lexis. THANKS TO AHRC…

11. Link between local patterns & text • If certain words and phrases have associations with the beginnings of texts… What are their functions at the textual level? • Mahlberg – Local Textual Functions

12. Textual Priming Project (AHRC): Aims • to investigate whether (and if so how many and what types of) lexical items are primed to appear in text-initial or paragraph-initial position • to identify lexico-grammatical patterns and see how these patterns can be functionally interpreted in the textual contexts. to relate these lexical and corpus-driven facts to current textual descriptions of (hard) news stories that might provide explanations for the positive primings of relevant lexis. THANKS TO AHRC…

13. Textual Priming Project (AHRC): Aims • to investigate whether (and if so how many and what types of) lexical items are primed to appear in text-initial or paragraph-initial position • to identify lexico-grammatical patterns and see how these patterns can be functionally interpreted in the textual contexts. • to relate these lexical and corpus-driven facts to current textual descriptions of (hard) news stories that might provide explanations for the positive primings of relevant lexis. THANKS TO AHRC…

14. Textual Priming Project: Method • Using ‘Home News’ section of Guardian (1998-2004; approx 52 million words) examine words in terms of their position: • TISC= text-initial sentences • PISC= paragraph-initial sentences (not in TISC) • NISC= non-initial sentences • (Single sentence paragraphs and headlines captured in other subcorpora SISC & HISC)

15. HISC TISC SISC Building ‘positional subcorpora’ Feathers fly as ‘bird cruelty’ in film is cut P1 (1) A fresh row over how animals can be used in movies erupted last night when the British board of film classification cut a scene from the Oscar-nominated Before Night Falls. P2 (2) The film’s American director, the artist-turned-filmmaker Julian Schnabel, immediately branded the decision to excise the scene in which the starving inmates of a Cuban jail catch a bird and eat it as "unfair and unnecessary", claiming some of the most memorable scenes in movie history would not pass muster if the law had been enforced with such zeal in the past. Fiachra Gibbons, ‘Feathers fly as “'bird cruelty”in film is cut’, The Guardian 7 June 2001.

16. PISC NISC NISC NISC Building ‘positional subcorpora’ P3 (3) “Did anyone ask the water buffalo that was hoisted off the ground by a helicopter in Apocalypse Now had it given its permission to be used in this way?’ he asked. (4) Had it been fully briefed and trained in aerial flight before its big scene? I ask you. (5) Did that poor animal, I wonder, have to have counselling for trauma afterwards? I don't think so. (6) I’m sure he just continued with his normal life chewing grass after he came back to earth again.” Fiachra Gibbons, ‘Feathers fly as “'bird cruelty”in film is cut’, The Guardian 7 June 2001.

17. Summary of positional subcorpora Guardian Home News 1998-2004

18. Summary of positional subcorpora Guardian Home News 1998-2004 Sentences Tokens TISC 4.8% PISC 25.9% SISC 23.7% NISC 45.48% TISC 6% PISC 24% SISC 32.9% NISC 37.1%

19. Textual Priming Project: Method • Identify items that are ‘key’ in TISC (Text-Initial Sentence Corpus) when compared with NISC (Non-initial Sentence Corpus) Examples include: yesterday, last night announced, suffered, stressed, according to a plans, report over, a, under, after, against fresh, branded

20. Textual Priming Project: Method • Identify items that are ‘key’ in TISC (Text-Initial Sentence Corpus) when compared with NISC (Non-initial Sentence Corpus) • Examples include: • yesterday, last night • announced, suffered, stressed, according to a • plans, report • over, a, under, after, against • fresh, branded

21. Three ways a key TISC word might differ from its NISC counterparts • It might simply differ in frequency, i.e. it is used the same way in TISC and NISC, but is used much more often proportionally in TISC • It might differ proportionally in use or certain usages might be absent from one or the other corpus, but the difference is a matter of degree • It might differ markedly in its use in TISC from NISC

22. Textual Priming Project: Method • Identify items that are ‘key’ in TISC (Text-Initial Sentence Corpus) when compared with NISC (Non-initial Sentence Corpus) • Examples include: • yesterday, last night • announced, suffered, stressed, according to a • plans, report • over, a, under, after, against • fresh, branded

23. Textual Priming Project: Method • Identify items that are ‘key’ in TISC (Text-Initial Sentence Corpus) when compared with NISC (Non-initial Sentence Corpus) • Examples include: • yesterday, last night • announced, suffered, stressed, according to a • plans, report • over, a, under, after, against • fresh, branded

24. expect.occs 57.2 229.2 313.6 354.0 per million wds 52.2 15.9 18.4 14.3 per 10000 sents 14.4 3.3 5.7 2.6 % of occs 17.1 20.9 33.0 29.0 Example: branded TISC PISC SISC NISC raw 163 199 315 277

25. Example: branded

26. Usage Patterns: branded TISC 163 NISC 277 Premod adj 5 (3.1%) Premod adj 41 (14.8%) 236 (85.2%) 157 (96.9%)

27. Usage Patterns: branded TISC 163 NISC 277 Premod adj 5 (3.1%) Premod adj 41 (14.8%) 236 (85.2%) 157 (96.9%) …a third of branded goods sold over the internet… …British branded clothes has been washed up… Fake branded products such as…

28. Usage Patterns: branded TISC 163 NISC 277 Premod adj 5 (3.1%) Premod adj 41 (14.8%) 236 (85.2%) 157 (96.9%) …an expensive branded drug on the NHS. …that sell branded goods at lower prices Premier League branded healthy living programme… …half is for branded medicines prescribed by GPs,… …of their branded products unless they… Next came branded restaurants and most…

29. Clause Type: branded branded MAIN VERB Subordinate other TISC (50%) NISC (40%) TISC (25%) NISC (33%) TISC (25%) NISC (27%)

30. Clause Type: branded branded MAIN VERB Subordinate other TISC (50%) NISC (40%) TISC (25%) NISC (33%) TISC (25%) NISC (27%)

31. Clause Type: branded branded MAIN VERB Subordinate TISC (67%) NISC (55%) TISC (33%) NISC (45%)

32. Patterns: branded TISC 48 (29.5%) of 163 NISC 42 (15.2%)of 277 for because after branded + X + + REASON …Charles Clarke branded the club a disgrace FOR refusing to sign up. Civic Leaders in Birmingham have appealed for funds to transform the subterranean New Street railway station which has been branded an embarrassment BECAUSE of the dingy first impression it offers visitors. Norman Tebbit was branded paranoid and a fantasist last night as Tory modernisers questioned his mental state AFTER the former cabinet minister claimed there was a plot to oust him from the party.

33. Patterns: branded TISC 135 (82.8%) of 163 NISC x (70.0%)of 277 branded + NEGATIVE TISC 35 (21.5%) of 163 NISC 48 (17.3%)of 277 branded+ QUOTES …branded “war criminals” yesterday……has branded as “totally ridiculous”… …branded as “institutionally racist”…

34. branded – Some brief points • negative priming in TISC for BRANDED GOODS • positive priming in TISC for collocation with yesterday • TISC/PISC – colligation with present perfect • TISC/NISC – use of quotes with NEG • negative priming for hypotheticals & Futures in TISC (with presence in NISC)

35. branded – local grammar • Process of ‘branding’ is a combination of VERBAL and ATTRIBUTIONAL The CARRIER always present X was branded Y Z branded X “Y” ASSIGNER – optional X was branded Y (by Z) Z branded X “Y” REASON following for, when, after

36. branded – local grammar • Process of ‘branding’ is a combination of VERBAL and ATTRIBUTIONAL • The CARRIER always present • X was branded Y • Z branded X “Y” • ASSIGNER – optional • X was branded Y (by Z) • Z branded X “Y” REASON following for, when, after

37. branded • Process of ‘branding’ is a combination of VERBAL and ATTRIBUTIONAL • The CARRIER always present • X was branded Y • Z branded X “Y” • ASSIGNER – optional • X was branded Y (by Z) • Z branded X “Y” • REASON following for, when, after

38. branded and News Values • White (1997) • Hard News stories have ‘Orbital Structure’ • Nucleus (core of which is captured in TISC) site for intensification and marking newsworthiness • Lexical intensification: • axed vs dismissed • shake-up vs reorganization • branded vs named/labelled Ask yourself, yes even Guardian readers ask yourselves, would you rather read about qualified majority voting or John Prescott being branded a male chauvinist by a woman French environment minister? Guardian, Dec. 2, 2000

39. Three ways a key TISC word might differ from its NISC counterparts • It might simply differ in frequency, i.e. it is used the same way in TISC and NISC, but is used much more often proportionally in TISC • It might differ proportionally in use or certain usages might be absent from one or the other corpus, but the difference is a matter of degree • It might differ markedly in its use in TISC from NISC

40. Three ways a key TISC word might differ from its NISC counterparts • It might simply differ in frequency, i.e. it is used the same way in TISC and NISC, but is used much more often proportionally in TISC • branded differs proportionally in use or certain usages might be absent from one or the other corpus, but the difference is a matter of degree • It might differ markedly in its use in TISC from NISC

41. expect.occs 294.0 1179.1 1613.0 1821.0 per million wds 296 86 94 67 per 1000 sents 8.1 1.8 2.9 1.2 % of occs 18.81 21.89 32.77 26.53 Example: fresh TISC PISC SISC NISC raw 923 1074 1608 1302

42. Example: fresh

43. Comparing Collocates: R1 position Top 20 R1 collocates with fresh in TISC Top 20 R1 collocates with fresh in NISC

44. Comparing Collocates: R1 position Top 20 R1 collocates with fresh in TISC Top 20 R1 collocates with fresh in NISC

45. fresh – Semantic Groups DISAGREEMENT

46. fresh – Semantic Groups DISAGREEMENT DIFFICULTIES(trouble)

47. BAD NOUN fresh – Semantic Groups DISAGREEMENT DIFFICULTIES(trouble) THREAT

48. fresh – Semantic Groups DISAGREEMENT DIFFICULTIES(trouble) THREAT INVESTIGATION evidence?

49. fresh – Semantic Groups DISAGREEMENT DIFFICULTIES(trouble) THREAT INVESTIGATION LIFESUSTAINING

50. Patterns in TISC: fresh SEMANTIC GROUP TISC DISAGREEMENTDIFFICULTIESTHREAT when12after3as4 SUFFER + fresh + L2 14L1 4L3+ 2 20 (0 NISC) NISC 1 instance ‘suffered a fresh setback when’