Today we will experiment with Twine, “an open-source tool for telling interactive, nonlinear stories.” The term “non-linear” stories is a broad one, and so some folks think of Twine as a platform for making electronic literature, while others consider it a platform for making games (while others question that distinction). Twine was used most famously to map out the story for the “Bandersnatch” episode of Black Mirror. There are many Twine games out in the world for folks to play.
You can use Twine online or download the application for your computer. Allison Parrish’s A Quick Twine (2.2+) Tutorial is a great introduction to the platform and some basic macros and variables that can extend the platform’s capabilities. We will refer to it throughout today’s lab.
I’ve also prepared a basic Twine interpretation of the first chapter of Moby Dick, which you can open in your browser and view or, more usefully, download and import into Twine so you can see how it is set up. If you download the HTML file, you can use the “Import from file” option within Twine to investigate the story’s structure. This is a pretty simple Twine structure, though I did try to build in a few macros that track, for instance, which pages a user has visited before allowing them to move on in the text.
If you already know Twine, or find yourself understanding its basic functions quickly, the Twine Cookbook provides robust documentation about Twine and its integrations, including JavaScript. The “Twine 2 Examples,” in particular, outline how to build in many more advanced features to a Twine story/game. The Extensions and Libraries page at Twine Resources also lists a number of integrations to extend Twine.
The basic premise for today’s lab report is simple: write it in Twine! You should use at least 2-3 more advanced features (e.g. variables or macros) or integration. Include at least one section in your Twine narrative that analyzes your process in light or our readings and discussions, as you do in other lab reports. You can upload the Twine HTML file in Canvas to submit your lab report.