Dimensions of variation in Hollywood: the language of comedy and drama

1. Dimensions of variation in Hollywood: the language of comedy and drama Marcia Veirano Pinto (apoio CNPQ)

2. Why study the language of Hollywood movies? • Hollywood movies are present in our every-day lives and are widely used in EFL classrooms, but research on their language is scarce; • Movie talk normally seeks to emulate spontaneous conversation in a variety of social activities. Thus, studying it may help us further understand how social activities and conversational functions motivate the choice of lexical and grammatical features.

3. Objective • To find the dimensions of variation in Hollywood comedy and drama across time.

4. Hypotheses • Movies are classified as comedy, drama, etc. which may predict their linguistic realization; • The language of movies seems to vary over time, and so there may be variation in the way movies are scripted over time; • Therefore two variables that might account for this variation are possibly : • movie genre (genre) • time (decade)

5. The corpus • Comprises the transcription of 32 movies between 1930 and 2009; • Features 16 comedies and 16 dramas - 2 comedies and 2 dramas per decade; • Has a total of 359,498 tokens and 8,506 types; • Each movie may have as few as 5,314 tokens or as many as 16,545 tokens; • On average, each movie has about 11,234 tokens.

6. Selection Criteria • The films were chosen: • with the help of the film guide “1001 filmes para ver antes de morrer” (2008) in which sixty-seven renowned film critics elected the best films of each decade; • as much as possible by their year of release so as to correspond to three different points in each decade: beginning, middle and end. This care was taken to avoid their bunching up in a single point in each decade. • based on the availability of: • movie on DVD + subtitles to be ripped (in Brazil only; importing DVDs would be costly and, more importantly, time consuming); • movie + transcription on the web;

7. Transcriptions • The time taken to transcribe every movie was reduced by the process of automatically extracting their subtitles from the DVDs with the help of the software DVDFab 6.0; • This step was necessary to guarantee that the texts in the corpus were true to the actual dialogues exchanged by the actors; • Ripped subtitles were preferred to transcriptions available on the web because they tend to be truer to what is actually heard, thus reducing the time taken to transcribe the movies.

8. Movies in the corpus

9. Movies in the corpus

10. Why map movies onto Biber’s 1988 dimension 1? • It is likely to throw light onto a very controversial issue: are texts that were written to be spoken good examples of spontaneous oral conversation? • Dimension 1 features comprise an array of linguistic features that are related to the difference between spoken vs. written texts, thus perhaps reflecting issues underlying variation across movies over time and across genres.

11. Biber’s Dimension 1: involved vs. informational production Private verbs THAT deletion Contractions Present tense verbs Second person pronouns DO as pro-verbs Analytic negation Demonstrative pronouns General emphatics First person pronouns Pronoun IT BE as main verb Causative subordination Discourse particles Indefinite pronouns General hedges Amplifiers Sentence relatives WH questions Possibility modals Non-phrasal coordination WH clauses Final prepositions Nouns Word length Prepositions Type/token ratio Attributive adjectives (Place adverbials) (Agentless passives) (Past participial WHIZ deletions) (Present participle WHIZ deletions)

12. Methodology: applying the multidimensional model • Collection of the corpus representing Hollywood drama and comedy; • Deciding on the linguistic features that are relevant to the research questions through literature; • Transforming the linguistic features into quantifiable variables; • Semi-automatic tagging of the corpus with a Shell script (Berber Sardinha, 2009) containing the tags for the features on Biber’s (1988) Dimension 1; • Manual checking of the tagging; • Standardizing of frequencies per 1,000 words to allow comparison of texts of different lengths;

13. Spreadsheet excerpt with variable values standardized by a 1,000

14. Methodology: applying the multidimensional model • Computing of the standardized score by subtracting Biber’s 1988 variable means on Dimension 1 from the variable means in the Movie Corpus and dividing them by Biber’s 1988 standard deviation.

15. Biber’s tag set

16. Methodology: applying the multidimensional model • The assigning of scores to the movies in the corpus with the equation : (positive standardized variable values) - (negative standardized variable values); • The plotting of the movie scores along the scale that represents Dimension 1. • The checking of the existence of a correlation between the variables genre and decade with the help of the software SPSS.

17. Descriptive statistics

18. Descriptive statistics

19. Descriptive statistics

20. |Telephone conversations (37.2) | 35 |Face-to-face conversations (35.3) | | 30 | | | 25 | | | 20 | Personal letters (19.5)/ spontaneous speeches (18.2)/ interviews (17.1) | | 15| | | 10| | | 5| | Romantic fiction (4.3) | Prepared speeches (2.2) 0| Adventure fiction (0.0) | Mistery fiction (-0.2)/ general fiction (-0.8) | Professional letters (-3.9)/ Broadcasts (-4.3) | -5 | | Science fiction (-6.1)/ Religion (-7)/ Humor (-7.8) | Popular lore (-9.3) -10| Editorials/ Hobbies (-10.1) | Biografies (-12.4)/ Press reviews (-13.9) | Academic prose (-14.9) -15| Press reportage (-15.1) | | Official documents (-18.1) Biber’s Dimension 1 INVOLVED PRODUCTION INFORMATIONAL PRODUCTION

21. Zooming in: involved production |Telephone conversations (37.2) | 35 |Face-to-face conversations (35.3) | | 30 | | | 25 | | | 20 | Personal letters (19.5)/ spontaneous speeches (18.2)/ interviews (17.1) | | 15| | | 10| | | 5| | Romantic fiction (4.3) | Prepared speeches (2.2) 0| Adventure fiction (0.0)

22. Zooming in: informational production 0| Adventure fiction (0.0) | Mistery fiction (-0.2)/ general fiction (-0.8) | Professional letters (-3.9)/ Broadcasts (-4.3) | -5 | | Science fiction (-6.1)/ Religion (-7)/ Humor (-7.8) | Popular lore (-9.3) -10| Editorials/ Hobbies (-10.1) | Biografies (-12.4)/ Press reviews (-13.9) | Academic prose (-14.9) -15| Press reportage (-15.1) | | Official documents (-18.1) -20|

23. Plotting movies on Dimension 1 INVOLVED PRODUCTION 40| |Telephone conversations (37.2) | 35 |Face-to-face conversations (35.3) | | 30 | | | 25 | | | 20 | Drama (20.2)/ Movies (20.2)/ Comedy (20.15)/Personal letters (19.5)/ spontaneous speeches (18.2)/ interviews (17.1) | | 15| | | 10| | | 5| | Romantic fiction (4.3) | Prepared speeches (2.2) | 0| Adventure fiction (0.0) | Mistery fiction (-0.2)/ general fiction (-0.8) | Professional letters (-3.9)/ Broadcasts (-4.3) | -5 | | Science fiction (-6.1)/ Religion (-7)/ Humor (-7.8) | Popular lore (-9.3) -10| Editorials/ Hobbies (-10.1) | Biografies (-12.4)/ Press reviews (-13.9) | Academic prose (-14.9) -15| Press reportage (-15.1) | | Official documents (-18.1) -20| INFORMATIONAL PRODUCTION

24. Zooming in 40| |Telephone conversations (37.2) | 35 |Face-to-face conversations (35.3) | | 30 | | | 25 | | | 20 | Drama (20.2)/ Movies (20.2)/ Comedy (20.15)/ Personal letters (19.5)/ spontaneous speeches (18.2)/ interviews (17.1) | | 15| | | 10| | | 5| | Romantic fiction (4.3) | Prepared speeches (2.2) | 0| Adventure fiction (0.0) INVOLVED PRODUCTION

25. Dimension 1: 1930 INVOLVED PRODUCTION 35| | | 30 | | | 25| | | 20| Movies (20.2) | |Drama (17.9)/ Comedy (17.9) 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | INFORMATIONAL PRODUCTION

26. Dimension 1: 1940 INVOLVED PRODUCTION 35| | | 30 | | | 25| | | 20| Comedy (20.67) |Movies (19.31) | Drama (17.96) 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | INFORMATIONAL PRODUCTION

27. Dimension 1: 1950 INVOLVED PRODUCTION 35| | | 30 | | | 25| |Drama (24.21) |Movies (19.31) 20| Comedy (20.30) | | 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | INFORMATIONAL PRODUCTION

28. Dimension 1: 1960 35| 30 | | | 25| | | 20| | Drama (19.08) |Comedy (17.36)/Movies (18.22) 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

29. Dimension 1: 1970 INVOLVED PRODUCTION | 30 | | | 25| |Comedy (23.69) |Movies (22.74) 20|Drama (21.78) | | 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | -20 | INFORMATIONAL PRODUCTION

30. Dimension 1: 1980 | 30 | | | 25| | | 20| Drama (20.66) |Movies (19.37) |Comedy (18.08) 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

31. Dimension 1: 1990 | 30 | | | 25| | | Comedy (21.64) 20| Movies (20.61) |Drama (19.58) | 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | -20| INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

32. Dimension 1: 2000 | 30 | | | 25| | |Movies (21.15) Comedy (21.55) 20| Drama (20.75) | | 15| | | 10| | | 5| | | | 0| | | | -5| | | -10| | | -15| | | -20| INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

33. Dimension 1 and comedy over the years | | 30 | | | 25 | |Comedy_1970 (23.69) |Comedy_2000 (21.55)/ Comedy_1990 (21.64) 20 |Movies (20.2)/Comedy_1940 (20.67)/ Comedy_1950 (20.30) |Comedy_1980 (18.08) |Comedy_1960 (17.36)/ Comedy_1930 (17.9) 15| | | 10| | | 5| | | | 0| | | | -5 | | | -10| | | -15| | | | -20| INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

34. Dimension 1 and drama over the years 35 | | | 30 | | | 25 | |Drama_1950 (24.21) |Drama_1970 (21.78) 20 | Movies (20.2)/ Drama_1980 (20.66)/ Drama_2000 (20.75) | Drama_1960 (19.08)/ Drama_1990 (19.58) |Drama_1930 (17.9)/ Drama_1940 (17.96)/ 15| | | 10| | | | 5| | | | | 0| | | | -5 | | | -10| | | -15| | | -20| INFORMATIONAL PRODUCTION INVOLVED PRODUCTION

35. Comedy and Drama over time | Manhattan (comedy/ 1979) 30| |Twelve angry men (drama_1957) | | | 25| | Mr. Deed’s goes to town (comedy/ 1936)/ American beauty (drama/ 1999)/ Some like it hot (comedy/1959) | The Lady Eve (comedy/1941 )/ Little Miss Sunshine (comedy/ 2006)/ |One flew over the cukoo’s nest (drama/1975)/ Groundhog day (comedy/1993)/ |The hustler (drama/1961 )/ Kramer vs. Kramer (drama/1979)/ Children of a lesser God (drama/ 1986)/ There’s something about Mary (comedy/1998)/ Crash (drama/ 2004)/ 20| Ghostbusters (comedy/1984)/ Lost in translation (drama/2009) | Rain man (drama/ 1988)/ It’s a wonderful life (drama/1946 )/ Meet the parents(comedy/2000) |Sunset boulevard (drama/1950)/ The Apartment (comedy/1960) | Mr. Smith goes to Washington (drama/ 1939)/ Only angels have wings (drama/1939)/ Philadelphia story (comedy/1940) | Citzien Kane (drama/1941)/ How to marry a millionaire (comedy/1953) Cool hand Luke (drama/1967)/ M*A*S*H (comedy/1972)/ Good morning Vietnam (comedy/1987)/ 15 |The producers(comedy/1968) | Philadelphia (drama/1993) | | | Duck soup(comedy/1933)/ 10| | | | | | | 0 |

36. Dimension 1: summary of results Twelve Angry Men represents well the involved end of factor 1 because it displays a great number of features that are typical of speech such as: personal pronouns, contractions, interjections, questions, among others. Twelve angry men excerpt Ok, fellows. Can wehold it down a minute? Sure. Fellows, say, we'd like to get started. Gentleman at the window. We'd like to get started. Oh, I'm sorry. Pretty tough to figure, isn't it? Kid killshis father, bang, just like that? Oh listen, if you had your eyes open you'd see that happens all the time. They let those kids run wild up there. Well, maybe it serveshim right, you know what I mean? Is everyone here? The old man is inside. Oh, would you knock on the door for him? Yeah. You a Yankee fan? No

37. Dimension 1: summary of results On the other hand, Duck soup is the movie with the lowest level of involvement because it doesn’t have as many variables for involved production as the others. Duck soup excerpt How do you do? Miss Marcal. We've met. Well, I hope His Excellency gets here soon. His Excellency makes it a point always to be on time. As long as I've known him, he's never been late to an appointment His Excellency is due to take his station beginning his new administration he'll make his appearance when the clock on the wall strikes ten.

38. Dendogram

39. Dendogram • This shows the result of cluster analysis, which is a statistical procedure to group cases into groups that share similar data; in my case, movies that have similar scores for factor 1. And it also shows you how those large groups break down into smaller groups and the other way round. It’s a hierarchical organization. • The dendogram shows two basic groups: one comprising movies from 18 to 28, at the top and the other from 5 to 17, qt the bottom, not in this exact order.

40. Cluster 1

41. Cluster 1 Cluster 1 shows some effect of time with older movies bunching up together here

42. Cluster 2

43. Cluster 2 Cluster 2, on the other hand, has sort of more recent movies; all of the 2000 movies and most of the 70’s

44. CONCLUSION • The existing classification for movies doesn’t promote understanding of their language variation; • Hollywood comedy and drama seem to be a register in their own right, that is, genre doesn’t seem to lead to any language variation; • There’s variation across individual movies, but the variables genre and decades do not explain it, but perhaps two big time groups, before and after the 1970’s regardless of genres.

45. CONCLUSION • There seems to be a grammar of movies that is similar to spontaneous conversation; • This means that they can be explored in the EFL classroom as a relatively good alternative for spontaneous conversation with some advantages: • Teachers have easy access to them; • They contextualize several linguistic features well, which is bound to help students learn not only the structure of grammatical features, but also their pragmatic and discursive uses. • Their plots and stories are likely to make them interesting for students; • All these coupled with the fact that their language tends to be less broken than spontaneous conversation may override the use of spontaneous conversation in the classroom.