{"id":390,"date":"2020-02-19T02:27:00","date_gmt":"2020-02-19T02:27:00","guid":{"rendered":"https:\/\/courses.digitaldavidson.net\/elit20\/?page_id=390"},"modified":"2020-04-04T20:36:23","modified_gmt":"2020-04-04T20:36:23","slug":"tracery-project","status":"publish","type":"page","link":"https:\/\/courses.digitaldavidson.net\/elit20\/tracery-project\/","title":{"rendered":"Tracery Project"},"content":{"rendered":"

One of our objectives<\/a> in DIG 220 is to \u201ccreate original multimodal work that takes advantage of the unique aesthetic and literary affordances of digital environments.\u201d To that end you will create a procedurally-generated narrative.<\/p>\n

Update:<\/strong> <\/span>Check out all the finished Tracery projects<\/a>!<\/p>\n

Overview<\/h2>\n

You’ll use a variation of the “slotted” technique of combinatory writing. This means building sentence templates with empty slots for nouns, verbs, and so on. A program then randomly selects from pre-selected lists of words to fill each slot. Think of procedural generation as Mad Libs<\/em> gone crazy. Tracery is the procedural engine you’ll use. It’s a Javascript library by Kate Compton that lets you create surprising configurations of texts out of the template (called “grammar”) and vocabulary you provide.<\/p>\n

Strictly speaking, this project does not involve programming. It does, however, require procedural thinking. Every Tracery grammar takes the form of JSON data. This is a highly structured text format that both humans and computers can \u201cread\u201d\u2014though parse<\/em> might be a better word. Your grammar data file tells Tracery what your templates are (templates in the plural because you can embed templates within templates recursively) and provides the vocabulary for Tracery to use as it fills in the templates.<\/p>\n

\"Screenshot<\/a>
The Tracery grammar JSON that powers Don\u2019t Drink the Water\u201d<\/a><\/figcaption><\/figure>\n

It\u2019s easy for text generation to be comical or satirical, like Nora Reed\u2019s thinkpiecebot<\/a> or Compton\u2019s Night Vale Generator<\/a>, both of which use Tracery. Other text generation parodies powered by tools similar to Tracery include the Postmodern Essay Generator<\/a> and Eric Drass\u2019s machine imagined art<\/a>.<\/p>\n

It\u2019s also possible to make text generators that are serious or provide social critique, such as my own Don\u2019t Drink the Water<\/a> or Leonardo Flores’ Tiny Protests<\/a> bot, which both use Tracery.<\/p>\n

Guidelines<\/h2>\n
    \n
  1. Decide what kind of text you want to generate. Will it be a parody? Social commentary? A genre, like horror, romance, or science fiction? Fake non-fiction? What\u2019s the mood of the work? Humorous? Sarcastic? Somber or melancholy? Whatever it is, strive to give it some depth.<\/li>\n
  2. Make an account on Glitch<\/a> and clone the template files<\/a> from “Don’t Drink the Water.” Glitch is a community of creative coders that provides free online tools and hosting. Once you’ve remixed the project<\/a> you can edit your own version directly in your browser. You can instantly see the results by clicking the “Show Next to the Code” option in Glitch (click the sunglasses). Also check out my tips on customizing the look<\/a> of your project.<\/li>\n
  3. Go through the Tracery tutorials below as you work on your project. When you first start it might help to use a visual editor. Beware that these editors are liable to crash as your grammar grows in complexity. You can paste the code from the visual editor into Glitch. See also my Tracery Tips<\/a> for more details on working with Tracery.<\/li>\n
  4. You will also write an Artist Statement that puts your Tracery project in dialogue with questions regarding combinatory writing, procedural generation, novelty and repetition, authorship, and creativity.<\/li>\n<\/ol>\n

    Criteria<\/h2>\n

    These are the minimal requirements for the project to be considered for a B-range grade.<\/p>\n