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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.
Teaching
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...
.txtLAB Internships 2016: Computational Cultural Advocacy

.txtLAB Internships 2016: Computational Cultural Advocacy

.txtLAB is pleased to offer four undergraduate internships for the coming academic year. This year’s theme is “Cultural Advocacy: Women in the Public Sphere.” The aim of the internship is to 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 bestow...
txtLAB450. A Multilingual Data Set of Novels for Teaching and Research

txtLAB450. A Multilingual Data Set of Novels for Teaching and Research

I am very pleased to be able to share a collection of 450 novels that we have assembled that were published in English, French, and German during the long nineteenth century (1770-1930). The novels are labeled according to language, year of publication, author, title, author gender, point of view, and word length. They have been labeled as well...

Intro to Literary Text Mining

It’s that time of year, so I’ve gone ahead and posted my new syllabus for Introduction to Literary Text Mining. It’s still a work in progress and probably always will be. However I’m beginning to get a sense of the various contours/spaces of the field and the ways those can be taught to students. The...

Another New Course! Graduate Seminar in “Cultural Analytics” offered this semester

Pleased to announce LLCU 609, “Cultural Analytics: The Computational Study of Culture.” It offers an overview of the field, with an emphasis on text analysis, stylistics, sentiment analysis, topic modelling, social network analysis and visual culture. So far we have eight different disciplines represented in a class of about 18 students. Nice to see how...
New Course! Big Data and Literature: Intro to Literary Text Mining

New Course! Big Data and Literature: Intro to Literary Text Mining

I’m posting the syllabus to my new course Introduction to Literary Text Mining for those who are interested. The most challenging part is teaching material that I didn’t experience myself as a student — the easiest, and often the best, way to teach is to build on great seminars you had as a student. Well, this...