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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.
Digital Theory
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, that even in an issue...
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...
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...
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...
Culture + Computation: New Syllabus in Cultural Analytics LLCU 614

Culture + Computation: New Syllabus in Cultural Analytics LLCU 614

  I am pleased to add this year’s syllabus for my graduate course, “LLCU 614, Cultural Analytics: The Computational Study of Culture.” The aim of the course is twofold: 1) to introduce students in the humanities to the computational and quantitative methods for studying culture in order to move beyond the use of anecdotal evidence and...
The Humanities: Theory Rich, Evidence Poor

The Humanities: Theory Rich, Evidence Poor

At some point, theory was declared over. Which was a polite way of saying we can get back to doing what we’ve always done. Which, it turns out, was theory. The humanities represent an amazing collection of individuals who have over the ages developed an extraordinary array of theories about people, the past, creativity, and social life....
Why your dissertation needs data

Why your dissertation needs data

Dear Future Graduate Students, It’s that time of year to start thinking about grad school. Recruiting is not easy for me. My general sentiment around graduate training is, let them decide. Advertising or persuasion is for places like Trump University not scholarship. But I think we are at a bit of a crossroads in our field...
Literary Text Mining Syllabus

Literary Text Mining Syllabus

It’s that time of year and so I’m posting my latest syllabus of my data and literature class. I have found over the years that every time I create a new class I always start with too much and gradually winnow as the years go by (until there is nothing left and I teach a...
CA Is  Here

CA Is Here

I am very pleased to announce the official launch of CA: Journal of Cultural Analytics. As we state in the journal’s mission statement: Cultural Analytics is a new journal dedicated to the computational study of culture. Its aim is to promote high quality scholarship that intervenes in contemporary debates about the study of culture using computational...
Validation and Subjective Computing

Validation and Subjective Computing

Like many others I have been following the debate between Matthew Jockers and Annie Swafford regarding the new syuzhet R package created by Jockers, which has been given a very nice storified version by Eileen Clancy. As others have pointed out, the best part of the exchange has been the civility and depth of replies,...
Beyond E-Books

Beyond E-Books

A new piece in World Literature Today that urges publishers to start thinking in terms of data sets and not just books.