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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.
NovelTM
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...
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...
Fictionality

Fictionality

I am pleased to announce the publication of a new piece I have written that appears today in CA: Journal of Cultural Analytics. The aim of the piece is to take a first look at the ways in which fictional language distinguishes itself from non-fiction using computational approaches. When authors set out to write an...
Identity: NovelTM Annual Workshop 2016

Identity: NovelTM Annual Workshop 2016

I am very pleased to announce the upcoming workshop for the NovelTM research group. This year’s theme is “Identity” and will be taking place at the Banff Research Centre in Banff, Alberta. For two days participants will meet and share new work that uses computational modelling to understand the various ways that novels construct identity...
CA Fall Preview: Food, Folklore and Lots of Novels

CA Fall Preview: Food, Folklore and Lots of Novels

We have some exciting new material that will be appearing shortly in CA: Journal of Cultural Analytics, which I thought I would share here. Dan Jurafsky, Victor Chahuneau, Bryan R. Routledge, and Noah A. Smith will have a new piece out on the relationship between food menus and social class. As they argue in their...
How Cultural Capital Works: Prizewinning Novels, Bestsellers, and the Time of Reading

How Cultural Capital Works: Prizewinning Novels, Bestsellers, and the Time of Reading

This new essay published in Post45 is about the relationship between prizewinning novels and their economic counterparts, bestsellers. It is about the ways in which social distinction is symbolically manifested within the contemporary novel and how we read social difference through language. Not only can we observe very strong stylistic differences between bestselling and prizewinning writing,...
Why are Jane Austen's novels so popular? Her characters are introverts.

Why are Jane Austen’s novels so popular? Her characters are introverts.

As part of the work on characterization in the novel that we’ve been doing recently in the lab, I’ve come across an interesting aspect of the classic nineteenth-century novel. It turns out that female main characters are far more cogitative and perceptive than their male counterparts. However, this appears only to be true for female...
Do Creative Writing Degrees Impact the Contemporary Novel?

Do Creative Writing Degrees Impact the Contemporary Novel?

I have a new piece out in The Atlantic with Richard Jean So. The piece addresses recent debates as to whether MFA programs have had a major impact on contemporary novels. The short version is that there is very little evidence to suggest any major differences between novels written by authors with MFA degrees and...
CBC interview on using algorithms to predict prizewinners and bestsellers

CBC interview on using algorithms to predict prizewinners and bestsellers

This past weekend I participated in an interview with Jeanette Kelly on the CBC to discuss our new work on using computers to predict bestsellers and prizewinning novels. In it I discuss the Devoir challenge in which local Quebec writers try to impersonate a bestseller using our data and our successful attempt at predicting this year’s Giller Prize winner...
Does the Canon Represent a Sampling Problem? A Two Part Series

Does the Canon Represent a Sampling Problem? A Two Part Series

The most recent pamphlet from the Stanford Literary Lab takes up the question of the representativeness of the literary canon. Is the canon — that reduced subset of literary texts that people actually read long after they have been published — a smaller version of the field of literary production more generally? Or is it substantially different?...
The Constraints of Character. Introducing a Character Feature-Space Tool

The Constraints of Character. Introducing a Character Feature-Space Tool

What is it that we do with characters? And what do they do for us? Different schools of literary theory have provided different answers to these questions. For the Russian formalists, character was above all else a “type,” one that served different narrative functions, a move that has been recently reawakened in the field of...
The .txtLAB Guide on How to Write Like a Bestseller

The .txtLAB Guide on How to Write Like a Bestseller

Here is a humble 1-page guideline that we produced after studying a sample of 10 years worth of the bestselling novels according to the NY Times Bestseller list. It was used as part of the Devoir Challenge in which some local Montreal writers were asked to try to write stories “like an American bestseller.” One of the most...