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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.
Disciplinarity
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, 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...
Academic Prestige and Publishing

Academic Prestige and Publishing

Very excited to announce the acceptance of a new article co-authored with Chad Wellmon that will be appearing in Critical Inquiry. The article, “Publication, Power, and Patronage: On Inequality and Academic Publishing,” addresses the unequal concentration of elite institutions within prominent humanities journals. Our goal is to begin to shed light on the academic publication system with a...