“Deep” Textual Hacks
A computational and pedagogical workshop

I put “deep” in scare quotes but really, all three words should have quotes around them—”deep” “textual” “hacks”—because all three are contested, unstable terms. The workshop is hands-on, but I imagine we’ll have a chance to talk about the more theoretical concerns of hacking texts. The workshop is inspired by an assignment from my Hacking, Remixing, and Design class at Davidson, where I challenge students to create works of literary deformance that are complex, intense, connected, and shareable. (Hey, look, more contested terms! Or at the very least, ambiguous terms.)

We don’t have much time for this workshop. In this kind of constrained setting I’ve found it helps to begin with templates, rather than creating something from scratch. I’ve also decided we’ll steer clear of Python—what I’ve been using recently for my own literary deformances—and work instead in the browser. That means Javascript. Say what you want about Javascript but you can’t deny that Daniel Howe’s RiTA library is a powerful tool for algorithmic literary play. But we don’t even need RiTA for our first “hack”:

What’s great about “Taroko Gorge” is how easy it is to hack. Dozens have done it, including me. All you need is a browser and a text editor. Nick never explicitly released the code of “Taroko Gorge” under a free software license, but it’s readily available to anyone who views the HTML source of the poem’s web page. Lean and elegantly coded, with self-evident algorithms and a clearly demarcated word list, the endless poem lends itself to reappropriation. Simply altering the word list (the paradigmatic axis) creates an entirely different randomly generated poem, while the underlying sentence structure (the syntagmatic axis) remains the same.

The next textual hack template we’ll work with is my own:

This little generator is essentially half of @_LostBuoy_. It generates Markov chains from a source text, in this case, Moby-Dick. What’s a Markov chain? It’s a probabilistic chain of n-grams, that is, words. The algorithm examines a source text and figures out which word or words are likely to follow another word or other words. The “n” in n-gram refers to the number of words you want the algorithm to look for. For example, a bi-gram Markov chain calculates which pair of words are likely to follow another pair of words. Using this technique, you can string together sentences, paragraphs, or entire novels. The higher the “n” the more likely the output is to resemble the source material—and by extension, sensible English. Whereas “Taroko Gorge” plays with the paradigmatic axis (substitution), Markov chains play along the syntagmatic axis (sentence structure). There are various ways to calculate Markov chains; creating a Markov chain generator is even a common Intro to Computer Science assignment. I didn’t build my own generator, and you don’t have to either. I use RiTA, a Javascript (and Processing) library that works in the browser, with helpful documentation.

The final deformance is a web-based version of the popular @JustToSayBot:

And I have a challenge here: thanks to the 140-character limit of Twitter, the bot version of this poem is missing the middle verse. The web has no such limit, of course, so nothing is stopping workshop participants from adding the missing verse. Such a restorative act of hacking would be, in a sense, a de-deformance, that is, making my original deformance less deformative, more like the original.

Digital Humanities at MLA 2015
Vancouver, January 8-10

Here is a list of more or less digitally-oriented sessions at the upcoming Modern Language Association convention. These sessions address digital culture, digital tools, and digital methodology, played out across the domains of research, pedagogy, and scholarly communication. If I’ve overlooked a session, let me know in the comments. You might also be interested in my short reflection on how the 2015 program stacks up against previous MLA programs. Continue reading

Digital Humanities and the MLA
On the state of the field at the MLA

Since 2009 I’ve been compiling an annual list of more or less digitally-oriented sessions at the Modern Language Association convention. This is the list for 2015. These sessions address digital culture, digital tools, and digital methodology, played out across the domains of research, teaching, and scholarly communication. For the purposes of my annual lists I clump these varied approaches and objects of study into a single contested term, the digital humanities (DH).

DH sessions at the 2015 convention make up 7 percent of overall sessions, down from a 9 percent high last year. Here’s what the trend looks like over the past 6 MLA conventions (there was no convention in 2010, the year the conference switched from late December to early January): Continue reading

Closed Bots and Green Bots
Two Archetypes of Computational Media

The Electronic Literature Organization’s annual conference was last week in Milwaukee. I hated to miss it, but I hated even more the idea of missing my kids’ last days of school here in Madrid, where we’ve been since January.

If I had been at the ELO conference, I’d have no doubt talked about bots. I thought I already said everything I had to say about these small autonomous programs that generate text and images on social media, but like a bot, I just can’t stop.

Here, then, is one more modest attempt to theorize bots—and by extension other forms of computational media. The tl;dr version is that there are two archetypes of bots: closed bots and green bots. And each of these archetypes comes with an array of associated characteristics that deepen our understanding of digital media. Continue reading

Difficult Thinking about the Digital Humanities

Five years ago in this space I attempted what I saw as a meaningful formulation of critical thinking—as opposed to the more vapid definitions you tend to come across in higher education. Critical thinking, I wrote, “stands in opposition to facile thinking. Critical thinking is difficult thinking. Critical thinking is being comfortable with difficulty.”

Two hallmarks of difficult thinking are imagining the world from multiple perspectives and wrestling with conflicting evidence about the world. Difficult thinking faces these ambiguities head-on and even preserves them, while facile thinking strives to eliminate complexity—both the complexity of different points of view and the complexity of inconvenient facts. Continue reading

DIG 210: Data Culture

A new course for the Digital Studies program at Davidson College. Influences for the syllabus abound: Lisa Gitelman, Lauren Klein, Ben Schmidt, Matt Wilkens, and many other folks in the digital humanities.

Course Description

“Data” is often considered to be the domain of scientists and statisticians. But with the proliferation of databases across nearly all aspects of modern life, data has become an everyday concern. Bank accounts, FaceTime records, Snapchat posts, Xbox leaderboards, CatCard purchases, your DNA—at the heart of all them is data. To live today is to breathe and exhale data, wherever you go, online and off. And at the same time data has become a function of daily life, it has also become the subject of—and vehicle for—literary and artistic critiques.

This course explores the role of data and databases in contemporary culture, with an eye toward understanding how data shapes the way we perceive—and misperceive—the world. After historicizing the origins of modern databases in 19th century industrialization and census efforts, we will survey our present-day data landscape, considering data mining, data visualization, and database art. We will encounter nearly evangelical enthusiasm for “Big Data” but also rigorous criticisms of what we might call naïve empiricism. The ethical considerations of data collection and analysis will be at the forefront of our conversation, as will be issues surrounding privacy and surveillance. Continue reading

Sites of Pain and Telling

The Expressive Work of Spaces of Torture in Videogames

At the 2014 MLA conference in Chicago I appeared on a panel called “Torture and Popular Culture.” I used the occasion to revisit a topic I had written about several years earlier—representations of torture-interrogation in videogames. My comments are suggestive more than conclusive, and I am looking forward to developing these ideas further.

Today I want to talk about spaces of torture—dungeons, labs, prisons—in contemporary videogames and explore the way these spaces are not simply gruesome narrative backdrops but are key expressive features in popular culture’s ongoing reckoning with modern torture. Continue reading