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Welcome to .txtLAB, a laboratory for cultural analytics at McGill University directed by Andrew Piper. We explore the use of computational and quantitative approaches towards understanding literature and culture in both the past and present. Our aim is to engage in critical and creative uses of the tools of network science, machine learning, or image processing to think about language, literature, and culture at both large and small scale.
Think Small: On Literary Modelling

Think Small: On Literary Modelling

This is the name of a new piece I have out in PMLA in a section called “Franco Moretti’s Distant Reading.” The first point I try to make is that calling it “Moretti’s Distant Reading” is indicative of literary studies’ continued penchant for great men. It is ironic, or telling,...
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Why are non-data driven representations of data-driven research in the humanities so bad?

Why are non-data driven representations of data-driven research in the humanities so bad?

One of the more frustrating aspects of working in data-driven research today is the representation of such research by people who do not use data. Why? Because it is not subject to the same rules of evidence. If you don’t like data, it turns out you can say whatever you want about people who do...
Data Visualization and Reading - An Interview

Data Visualization and Reading – An Interview

Mark Algee-Hewitt and I recently took part in an interview with Elyse Graham for a special issue of English Studies on “Data Visualization and the Humanities.” You can read her introduction here and our interview here. We touch on a bunch of topics about visualization: like whether data visualization is exclusively exploratory, whether the humanities...
Cultural Advocacy Internship - "Gender Bias in Book Reviews"

Cultural Advocacy Internship – “Gender Bias in Book Reviews”

We are excited to announce the 2017-2018 Internship in Cultural Advocacy, focusing on gender bias in book reviews. The internship will address how women are both mis-represented and under-represented in the public discourse of book reviewing. Book reviews represent a significant cultural outlet that bestows authority, but as our lab’s new website called “Just Review” shows, there are a...
LLCU 255: Intro to Literary Text Mining -- New Syllabus 2017

LLCU 255: Intro to Literary Text Mining — New Syllabus 2017

Less but better. That’s the essentialist’s motto and that’s the one I use every year when I revise my syllabus. I keep removing things and students keep learning more every year. While there is clearly a ceiling for this approach, it works remarkably well as a pedagogical tactic. Here’s the full syllabus. This year’s class...
Data, data, data. Why Katherine Bode's new piece is so important and why it gets so much wrong about the field

Data, data, data. Why Katherine Bode’s new piece is so important and why it gets so much wrong about the field

Katherine Bode has written an excellent new piece asking us to reflect more on the data we use for computational literary studies. Her argument is that many of the current data sets available, which rely on date of first publication as a criteria for selection, miss the more socially imbedded ways literary texts have circulated...
Congratulations to this year's students!

Congratulations to this year’s students!

We have had an excellent year at .txtLAB. I want to send out a special thanks to all of the students who have been contributing to the lab. You’ve made it a great place to work. Here is a list of projects that we’ve been working on this year: studying the ambiguity surrounding social interactions...
Just Review, a student led project on gender bias in book reviewing

Just Review, a student led project on gender bias in book reviewing

For years, women have been aware that their books are less likely to get reviewed in the popular press and they are also less likely to serve as reviewers of books. Projects like VIDA and CWILA were started to combat this kind of exclusion. Over time they have managed to make some change happen in the industry....
The Eleanor and Park Challenge

The Eleanor and Park Challenge

Eleanor & Park is a beautiful young adult novel about two kids who fall in love after meeting, as so many kids do, on the school bus. It also contains a perfect challenge for the computational study of culture. Think of it as an alternative to the Turing test. Here’s the back story. We’ve begun studying...
Connectivity. A Conference

Connectivity. A Conference

Looking forward to this event tomorrow. Bringing together researchers from different disciplines to develop models of cultural connectivity. Connectivity has become the dominant framework through which contemporary knowledge is increasingly understood. From networks to clouds to close reading to reconstructing historical social worlds, making connections is at the core of what academics are expected to do. And...
Is Open Science a Neo-Liberal Tool? Here's why not.

Is Open Science a Neo-Liberal Tool? Here’s why not.

Last week Philip Mirowski gave a spirited polemic at Concordia University called, “What is Open Science supposed to fix?” Openness has become the new buzzword du jour. Who would be against openness? But do we really know what this word means? Over the course of an hour Mirowski made the case that open science is nothing less...
LIWC for Literature: Releasing Data on 25,000 Documents

LIWC for Literature: Releasing Data on 25,000 Documents

Increasing emphasis is being placed in the humanities on sharing data. Projects like the Open Syllabus Project, for example, have made a tremendous effort in discovering, collecting, and cleaning large amounts of data relevant to humanities research. Much of our data, however, is still locked-up behind copyright and paywalls within university libraries, even when the underlying...
Congratulations to Eva Portelance ARIA Intern for 2016

Congratulations to Eva Portelance ARIA Intern for 2016

Eva Portelance presented her work this past week that was completed under an Arts Undergraduate Research Internship (ARIA). Her project focuses on the computational detection of narrative frames. It involves three steps that include a theoretical definition of a frame, writing code to detect narrative frames and comparing those to existing methods of text segmentation, and...