using computer tools to analyze the words in “judge dredd”

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Using computer tools to analyze the words in Judge Dredd Slide 2 Beginnings considering the whys, whats and hows Methodological issues Analysis and some results Conclusions limitations and further research Slide 3 2000 AD first appeared in 1977 Judge Dredd appeared in issue 2 Publishers 1977: IPC/Fleetway Publishers Now: Rebellion Developments (large gaming developer) Slide 4 Slide 5 Been around for over 100 years Originally : funny - comical / satirical Poor quality (printing) Considered poor quality (literature) Slide 6 Largely ignored Commentaries on linguistics features often vague Slide 7 [] comics are a language [] which has its own syntax, grammar and conventions, and which can communicate ideas in a totally unique fashion. (Sabin,1996:8). Slide 8 Long history 1977 to present day Same author contributed over that time Access to data Slide 9 Just the words of the comic strip are being analyzed No visual analysis Investigating whether the comic strip has changed diachronically Also whether there are any stable language features Slide 10 I want to compare Judge Dredd at two points in time (1977 and 2003) I have some comics from 1977 and from 2003 How do I do the analysis? How many comics do I need to analyse? What do I analyse? Slide 11 1977 All the words from 52 episodes of Judge Dredd 2003 All the words from 52 episodes of Judge Dredd comparison Slide 12 Not all 52 weeks collected Just one author used (John Wagner) Stopped collecting at around 10000 words Time constraints Slide 13 Corpus name Years used Number of words Number of texts Average words/edition JD7778C1977/781112717655 JD0203C2002/031066419561 Slide 14 Corpus name Years used Number of words Number of texts Average words/sentence JD7778C1977/7811127177.31 JD0203C2002/0310664196.69 Slide 15 Comic strips: combine words and pictures consist of a number of components (see, for example, McCloud 1994) Slide 16 Slide 17 Speech Balloons Slide 18 Thought Balloons Slide 19 Captions Slide 20 Analyses data using an existing framework (or existing categories) Separates data into categories Forces decisions about data Exposes data that does not fit into categories Can suggest new categories (driven by data) Slide 21 Sound FX Slide 22 Picture Text Slide 23 Slide 24 Analysis based on forms what the various components look like. Speech/thought balloons, and captions look like speech/thought balloons and captions. but what about their content and function? Slide 25 Consistently higher frequencies of: prounouns you / I / we contractions s / nt negation nt Slide 26 Consistently lower frequencies of: the / of fewer nouns / less post modification of nouns conjunctions and / that Slide 27 you, your, youre, youve, ya all these pronouns require an addressee and indicate involvement with that addressee indicates that speech balloon data not only involves characters talking, but talking to an addressee, interaction between characters is important in comic strip narrative. Slide 28 I, Im, Me seems to indicate that characters also talk about themselves, or to themselves. 50% of occurrences of Im are followed by an ing-participle. shows characters interacting helps to tell whats happening (running commentary) Progressive aspect - on going action Slide 29 got 33% of instances of got involve HAVE, forming a semi-modal relating to obligation or necessity adds a sense of urgency or a degree of compulsion to what the characters say. heightens the sense of drama in the story. Slide 30 Ive got to get a recharge weve got to get away from here youve got to get out of this Slide 31 Get 20% in imperative structures get away from me get after him get that garbage cleaned up Slide 32 gotta and gonna The orthographic representations of spoken language are more prevalent in JD7778C than JD0203C seems to reflect the characterization involved in certain stories (baddies). Slide 33 She / her In JD0203C female pronouns more frequent Female characters more prevalent and important. Slide 34 Expletives drokk has remained a feature of the comic strip over the twenty-five year history JD0203C - some extra expletives: grud, damn, and freakin, Slide 35 In JD7778C, the and of more frequent Also meanwhile, soon, suddenly, later And ahead behind In JD0203C pronouns he, him, she, her, it more frequent Differences reflect change in caption usage Slide 36 In the heart of Mega-City 1, huge metropolis of the 22 nd Century, lies a giant building, Mega-City 1. Vast metropolis of the 22 nd Century. Slick Willy pointed to a map of the old New York subway Two Troggies were left to guard the work squad. The minutes ticked by Dredd pulled away some of the rubble Slide 37 Dredd had the bit between his teeth. He wouldn't let up. They'd look into Bubba OKelly, find the connection. He'd tried to put things right, only made them worse. Killed a civilian But he'd been right! If they'd only opened their eyes to see... He'd been doing good work Slide 38 Slide 39 In JD7778C captions seem to be 3 rd person narration. In JD0203C the captions often similar to internal monologue Slide 40 Only used in one story in JD0203C Used more in JD7778C Provide a running commentary bring the reader up to speed with events in the story. Slide 41 HOW LONG HAVE I BEEN OUT...? MUST'VE PULLED ME CLEAR... SOMETHING'S GOING ON IN THAT BRAIN AND IT'S NOT JUST BLOOD LUST. NOT GIVING UP ON YOU YET, PAL... ! PRAGER'S GOT TROUBLE! I'VE STUMBLED ON AN UPRISING! NO CATCHING THEM NOW... THEY THINK GILL'S GOING TO SQUASH EASY. THEY DON'T KNOW WHAT THEY'RE UP AGAINST. Slide 42 Subject / dummy subject deletion attempts to show that thoughts consist of sentence fragments rather than complete sentences an attempt to differentiate thinking from talking Slide 43 Slide 44 Use of conjunction but also creates tension/drama So far so good but the rookies still got to rescue the Anderson boy That cadets skills are good, but hes not watching the alley up ahead Slide 45 Slide 46 JD7778C: HA, CLUNK, CRASH, AAAGH, AAAIEEE, AAARGH, BAROOM, BBAM, GULP, HAAAH, KERAAM, KERANG, NOOOOOOOO, SPLAT, SPLOSH, SPLOT, THUNK Slide 47 JD0203C: BDAM, BONG, BLEE, PING, FTOOOM, WHISSSSHH, AAAHH, BUDDA, BZZZ, SHRANGGG, SPANG, SSIFFFFF, SWAKK, VZZATTTTTT, AAIEE, BDAMM, BLAMM, CHUNKK, CLANGGG, FTOMPHH, FWOOOMPHHH, GGGRUNCHH, GLURRR, GRRAAARRRR, GRRRNNNNNNN, KERRANGGGG, KRAKKOOOOOOMM, KRUNNGGG, KZANNG, NRRRRR, SHRANNGG, SKASHH, SKRREEEEEEEEEE, SLASH, SPAK, SPAPPPP, SPLATT, SPLOT, SWAKKKKKK, SZZZ, THRUMMM, THUD, THWAP, UHHH, UNGH, UNNFFFFF, URRNHH, VAWOOOOOOOM, WHUMPHH, WHUNK, WHOINININ, YAAAAYYYYYYYYY, ZINNG, ZWAKK Slide 48 Sound effects more prevalent in JD0203C than they are in JD7778C Greater variety of sounds Adds a soundtrack to the actions Better printing seems to allow more to be going on in the picture without loss of clarity or cluttering. Slide 49 Category very small for both datasets Some represents writing letters etc. important to the story Other PT adds detail to the pictures Can help to form meaning or provide extra information Slide 50 Slide 51 Issue what counts as picture text? Is the category adequate? Applying categories to data form of interpretation Slide 52 Speech Balloons contain most of the words Features of spoken language Captions used differently in JD0203C Thought balloons more frequent in JD7778C Sound effects more frequent in JD0203C Picture text difficult to draw conclusions. Slide 53 Pictures seem to do more of the story telling. Slide 54 Practical issues collecting data Methodological issues representativeness, generalizability Slide 55 This study deals with only one comic strip from one comic Not possible to make generalizations about the language of all comic strips Any findings only relate to the language used in Judge Dredd as featured in 2000AD when written by John Wagner. Slide 56 However, this study could be seen as a start in the description of what constitutes comic strip language. And I would suggest that some of the features found here will be found in other comic strips. Slide 57 Comic strips are fictional narratives that contain mainly characters words Interactions between characters Slide 58 Its possible Other modern comic strips will let the pictures tell the story use fewer words than might have been used in the past But these things would have to be explored using more data. Slide 59 Look at more comic strips (past and present) Different sub-genres humorous etc. More detailed analysis of how the various components work (captions - internal monologue) Picture text Multi-modal analysis Slide 60 Eisner, W. (1996) Graphic Storytelling & Visual Narrative McCloud, S. (1994) Understanding Comics: The invisible Art Sabin, R. 1996 Comics, comix & graphic novels: A history of comic art Saraceni, M. (2003) The Language of Comics