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Using computer tools to analyze the words in “Judge Dredd ”. A diachronic investigation of the comic strip “Judge Dredd ”. Lecture structure. Beginnings – considering the whys, whats and hows Methodological issues Analysis and some results Conclusions – limitations and further research.

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Using computer tools to analyze the words in judge dredd

Using computer tools to analyze the words in “Judge Dredd”

A diachronic investigation of the comic strip “Judge Dredd”.


Lecture structure
Lecture structure

  • Beginnings – considering the whys, whats and hows

  • Methodological issues

  • Analysis and some results

  • Conclusions – limitations and further research


2000ad and judge dredd
2000AD and Judge Dredd

  • 2000 AD first appeared in 1977

  • “Judge Dredd” appeared in issue 2

  • Publishers 1977: IPC/Fleetway

  • Publishers Now: Rebellion Developments

    • (large gaming developer)

  • http://www.2000adonline.com


  • 2002

    1977


    Why a comic strip
    Why a comic strip?

    • Been around for over 100 years

    • Originally :

      • funny - comical / satirical

      • Poor quality (printing)

      • Considered poor quality (literature)


    Why a comic strip1
    Why a comic strip?

    • Largely ignored

    • Commentaries on linguistics features often vague


    Why a comic strip2
    Why a comic strip?

    • “ […] 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).


    Why judge dredd
    Why Judge Dredd?

    • Long history 1977 to present day

    • Same author contributed over that time

    • Access to data


    What is being investigated
    What is being investigated?

    • 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


    How?

    • 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?


    How?

    1977

    All the words from 52 episodes of Judge Dredd

    2003

    All the words from 52 episodes of Judge Dredd

    comparison


    Dataset building
    Dataset building

    • Not all 52 weeks collected

    • Just one author used (John Wagner)

    • Stopped collecting at around 10000 words

    • Time constraints




    Components of a comic strip
    Components of a comic strip

    • Comic strips:

      • combine words and pictures

      • consist of a number of components

      • (see, for example, McCloud 1994)


    Panels
    Panels

    and

    Gutters


    Speech balloons
    Speech Balloons

    Speech Balloons


    Thought balloons
    Thought Balloons

    Thought Balloons


    Captions
    Captions

    Captions


    Component analysis
    Component analysis

    • 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)


    Sound effects
    Sound Effects

    Sound FX


    Picture text
    Picture Text

    Picture Text



    Component analysis1
    Component analysis

    • 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?


    Speech balloons1
    Speech balloons

    • Consistently higher frequencies of:

      • prounouns – you / I / we

      • contractions– ‘s /n’t

      • negation–n’t


    Speech balloons2
    Speech balloons

    • Consistently lower frequencies of:

      • the / of – fewer nouns / less post modification of nouns

      • conjunctions – and / that


    Speech balloons3
    Speech balloons

    • you, your, you’re, you’ve, 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.


    Speech balloons4
    Speech balloons

    • I, I’m, Me

      • seems to indicate that characters also talk about themselves, or to themselves.

      • 50% of occurrences of I’m are followed by an ing-participle.

      • shows characters interacting

      • helps to tell what’s happening (running commentary)

      • Progressive aspect - on going action


    Speech balloons5
    Speech balloons

    • 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.


    Speech balloons6
    Speech balloons

    “I’ve got to get a recharge”

    “we’ve got to get away from here”

    “you’ve got to get out of this”


    Speech balloons7
    Speech balloons

    • Get

    • 20% in imperative structures

      “get away from me”

      “get after him”

      “get that garbage cleaned up”


    Speech balloons8
    Speech balloons

    • 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).


    Speech balloons9
    Speech balloons

    • She / her

      • In JD0203C – female pronouns more frequent

      • Female characters more prevalent and important.


    Speech balloons10
    Speech balloons

    • Expletives

    • drokk has remained a feature of the comic strip over the twenty-five year history

    • JD0203C - some extra expletives: grud, damn, and freakin,


    Caption data comparison
    Caption data - comparison

    • 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


    Jd7778c examples
    JD7778C - examples

    “In the heart of Mega-City 1, huge metropolis of the 22ndCentury, lies a giant building,”

    “Mega-City 1. Vast metropolis of the 22nd 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”


    Jd0203c examples
    JD0203C - examples

    “Dredd had the bit between his teeth. He wouldn't let up. They'd look into Bubba O‘Kelly, 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”



    Thought balloons1
    Thought balloons

    • 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.


    Thought balloons jd0203c
    Thought balloons – JD0203C

    • 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.


    Thought balloons jd0203c1
    Thought balloons – JD0203C

    • Subject / dummy subject deletion

    • attempts to show that thoughts consist of sentence fragments rather than complete sentences

    • an attempt to differentiate thinking from talking



    But …

    Use of conjunction but also creates tension/drama

    “So far so good – but the rookie’s still got to rescue the Anderson boy”

    “That cadet’s skills are good, but he’s not watching the alley up ahead”



    Sounds effects
    Sounds effects

    • JD7778C:

      HA, CLUNK, CRASH, AAAGH, AAAIEEE, AAARGH, BAROOM, BBAM, GULP, HAAAH, KERAAM, KERANG, NOOOOOOOO, SPLAT, SPLOSH, SPLOT, THUNK


    Sound effects1
    Sound effects

    • 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


    Sound effects2
    Sound effects

    • 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.


    Picture text1
    Picture text

    • 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



    Picture text2
    Picture Text

    • Issue – what counts as picture text?

    • Is the category adequate?

    • Applying categories to data – form of interpretation


    Summary
    Summary

    • 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.



  • Issues limitations
    Issues / Limitations

    • Practical issues – collecting data

    • Methodological issues – representativeness, generalizability


    Issues limitations1
    Issues / Limitations

    • 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.


    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.


    Generalisations
    Generalisations (?) description of what constitutes comic strip language.

    • Comic strips are fictional narratives that contain mainly characters’ words

    • Interactions between characters


    Generalisations1
    Generalisations (?) description of what constitutes comic strip language.

    • It’s 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.


    Future research
    Future research description of what constitutes comic strip language.

    • 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


    Some possible reading
    Some possible reading ... description of what constitutes comic strip language.

    • 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


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