The Augmented Criticism Lab’s Sonnet Database

This is the text of a short paper I delivered at the Digital Humanities 2019 conference in Utrecht, the Netherlands on 12 July 2019. The Augmented Criticism Lab’s Sonnet Database is in beta release.

To keep to my 10 minutes, I’ll be as focused as possible. My aim is to raise a research question, and then to describe my methods for answering it.

My question is:

Is the sonnet a form or a genre?

My method for answering it is:

A database of sonnets for text-analysis.

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Text-Analysis Unconference: Treating Texts as Data

REGISTER NOW for this event at the University of Calgary’s Taylor Family Digital Library

If texts – from survey transcripts to Shakespearean drama to social-media posts — are the objects of your research, you might benefit from using a computer to extend your analysis. Benefits include counting words, identifying topics, or analyzing sentiments. Text analysis is complex, but you don’t need a degree in statistics or computer science to use its tools. For instance, they can do simple comparisons between texts, like comparing the most frequent words in one text to those in another.

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Iter at 20: A Look Forward

This is the text of my paper delivered at a New Technologies in Renaissance Studies panel at the 2019 Renaissance Society of America meeting in Toronto.

Introduction

Despite my title, I am not a futurist. I am a born optimist who looks forward to many things, but more in the aspirational more than the predictive sense. As the great Wayne Gretzky used to say, I try to skate where the puck is going, rather than where it is.

So in this paper I’ll take a brief look backward at Iter’s history, and its organization of information that becomes knowledge that becomes wisdom about history. Then I’ll look forward to its future in the conjoined realms of discovery and dissemination, and in the realm of collaborative “spaces for possibility and play,” in Liz Grumbach’s words this morning.

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John Donne and the Sonnet Problem


What makes a sonnet? For most early modern examples, the answer is clear: a 14-line rhyming poem, its form either Shakespearean (three quatrains and a couplet) or Petrarchan (an octave and a sestet). There are exceptions to those formal rules, but most sonnets meet them.

Formal rules are the conventional answer. And that answer works for conventional sonnets, which are the vast majority of sonnets.

But if you enforce formal rules too rigorously, you encounter a few interesting problems. These are the problems that my project is investigating. Moments’ Monuments: The ACL Database is collecting as many sonnets as possible, so I can get a more definitive answer to this question: Is the sonnet a form or a genre? The trouble is, you need to decide first what qualifies as a sonnet.

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A Gentle Introduction to NLP

I’m giving a workshop at the University of Calgary’s Language Research Centre on the 16th of November 2018 (Craigie Hall D420, 9-10:30 am). Here’s the abstract:

A Gentle Introduction to Natural Language Processing

Natural Language Processing (NLP) is less intimidating than its name suggests. It’s just using a computer to process texts written in ‘natural’ (i.e. non-computer) languages like English, Estonian, or Esperanto. It slices those texts into lists of words, and then it does things with those words: counting, sorting, categorizing, comparing, transforming, substituting, and visualizing them. (Here’s my introduction and tutorial on some of these basic functions.) NLP is behind every phrase you Google, and every query you pose to Siri or Alexa; but what concerns us in this workshop is its potential for language research. You’ll learn how to collect and process texts, and how to run algorithms that quantify your qualitative inquiries. A case study will be my work detecting rhetorical figures like chiasmus in Shakespeare (“Fair is foul, and foul is fair”). To benefit from this workshop you need no programming experience, only a willingness to treat texts as data.

NLP for Literary Critics: An Introduction and Tutorial

Preface: Knowledge and Information

Shall I compare thee, human, to a machine? Thou art more critical and more intemperate (Shakespeare, Sonnet 18).

But seriously: how do human readers compare to machines? I ask because I want to define how literary critics can use machines to augment and extend our readings. Figuring that out depends on an understanding of how our readings compare to the machine’s abilities. Sure, they’re faster: but faster at what, exactly?
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Text Accordians

I write, with my keyboard, all day. Every day. E-mails, lecture notes, grant applications, status updates, first drafts, second drafts, slideshow bullets, blog posts. To paraphrase the great Johnny Cash, I type everywhere, man.

And along the way, I find I quite often need to write the same words and numbers. I close every e-mail the same jaunty way (“yours, Michael”); I give students the same directions to my office; I repeat the same writing advice in my grading; my phone number hasn’t changed in a decade.

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