Computational Models of Discourse Analysis

1. Computational Models of Discourse Analysis Carolyn Penstein Rosé Language Technologies Institute/ Human-Computer Interaction Institute

2. Warm-Up • Find examples of Foregrounding and Co-articulation in the analyses you did as well as mine • What are the equivalent of these in Gee’s theory if any?

3. Student Question • Quickies: what is the difference for our purposes between a system and a model. What is the difference between systemic and systematic in the context of Discourse analysis?

4. Foregrounding and Coarticulation • Foregrounding: how does the text make some things stand out over others? • Coarticulation: systems working together to achieve a particular effect

5. Guidelines • Identifying the genres • Helps to find an organizing principle • Using formatting and periodicity to identify how field unfolds • But remember that formatting only reflects discourse structure! • 3 analyses, all different genres • Analysis 1:recount, time as an organizing principle • Analysis 2: report, using contrasts for emphasis • Analysis 3: autobiographical recount, assuming story of life frame sets up expectations, and using negation and concession to address those

6. Where are the rows and columns?

7. Confused?

8. Student Quote • I've read each of the Martin and Rose readings several times but can't tell if there is a general technique they are using to analyze different works or if the analyses are all genre specific.

9. Student Quote • It seems to me that Gee's approach to introducing analysis was a lot more stand-off-ish. In chapter 8, Martin and Rose not only have the idea of "genre" but specific genres (i.e., recount, etc). I wonder if Martin & Rose have a list of potential genres (accompanied by a list of features that denote them, as done in this chapter?). Not knowing where the bounds of Martin & Rose are makes analysis a bit confusing.

10. Wondering where this was? Student Quote “Having read the assigned chapters from Martin and Rose I feel like I'm missing the trees of the forest. The text defines a lot of terms but doesn't seem to build a system out of it. For example it did not describe any procedural approaches to the analysis. I kept wondering if the missing chapters had the answer and I had a hard time interpreting chapter 8.”

11. Starting by observing overall organization ** In the absence of predefined system maps, look for things that “go together as a set” and could be used to structure the text.

12. Other Confusing Vocab • Not critical at this stage • Roles of sentences within paragraphs • hyperTheme: introduces the topic before details are given • hyperNews: ties together what was given already into a generalization • Roles of paragraphs in the larger text • macroTheme: introduces the topic before details are given • macroNews: ties together what was given already into a generalization

13. Student Quote • I actually find it difficult to converge on an argument when using SFL style analysis. It seems like there are a million different tools to analyze the text with and I can pick it apart along so many different dimensions, that when I look at it I see it for the textual and linguistic features rather than for the story about the person speaking. I'm looking for all of these cues from periodicity, engagement, appraisal, etc. and it's easy to get caught up in them, and seeing those patterns as the end goal to discover, rather than look at what they're being used for by the author.

14. “student” quote • I think that some of the confusion around Martin and Rose may come from our not knowing how the previous chapters are structured (which I vaguely do, having read most of the book). While Gee's approach seems to discuss how form is linked to function and that semantic function is a complex matroshka doll set of meanings in contexts, Martin and Rose seem to be more about examining "pure" form and without discussing exactly how to proceed from form to function. In a way this makes Martin and Rose's work easier to implement computationally, but it makes it harder to do so with a further goal in mind as the human "meaning maker" is implicit where Gee has attempted to make meaning making explicit. In other words, even with Martin and Rose's forms, how would we use a computational approach to gain in semantics? • I get the feeling that Martin and Rose's tools allow us to justify a pre-existing opinion, whereas Gee's tools allow us to examine more systematically the analytic options present within a text.

15. Student Quote • Slowly I'm beginning to appreciate the open nature of Gee's approach. Instead of a fixed system by which to analyze a text using SFL, Gee proposes that texts and discourses are so widely different through their human diverse aspects that imposing one system onto which we map a text is fairly unfeasible. Of course on the other hand it makes Critical Discourse Analysis much harder to cast into a software algorithm.

16. Other comparisons? • What frustrations do you have with Gee and/or Martin&Rose? • What is different or similar about the kinds of insights into language that you get from them? • What do you see that distinguishes different types of language: interviews, newsgroup threads, blogs, movie scripts, literature…? • Which one do you think you would choose to use and why?

17. Quote from Chapter 9 ** Keep this in mind as a challenge!!!

18. Where do we go from here?

19. Assignment 1 (not due til Feb2) • Transcribe a scene from a favorite move, play, or TV show • As a shortcut, you can find a script online • Excerpt should be no more than one page of text • Select one of the methodologies we are discussing in Unit 1 (e.g., from Gee, Martin & Rose, or Levinson) • Do a qualitative analysis of the data and write it up • Use readings from Unit 1 as a collection of models to chose from • Due on Week 4 lecture 2 • Turn in data, raw analysis (can be annotations added to the data), and write up (your interpretation of the analysis) • Not required now!! Prepare a powerpoint presentation for class (no more than 5 minutes of material) • Other Ideas: Twitter data, Google Groups, transcribe a real conversation (if your conversational partners agree…)

20. Questions?

21. Metafunctions