Racial Critique, Data Science, and Literary Studies

IGEL2022
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#1

:speech_balloon: Speaker: Richard Jean So

:classical_building: Affiliation: McGill University, Canada

Title: Racial Critique, Data Science, and Literary Studies

Abstract This talk explores the affordances of new methods in data science, such as machine learning, for the analysis of literature and culture. It will argue that a critical and reflexive use of such methods can facilitate new discoveries for literary studies, and that the two paired together can represent an important new form of cultural analysis, particularly for the study of race and literature. The talk is anchored by a case study that explores the post-war US novel, especially Black and Asian American fiction in a comparative racial context.

:movie_camera: Richard Jean So, Racial Critique, Data Science, and Literary Studies - YouTube

IGEL2022 conference schedule
#2

Great talk!

You looked at how 2 literary institutions (publishers-bestsellers and critics-prizes) reflect racial biases, I was wondering if looking at a third institution like libraries would show a different pattern?

There are many concurring reasons motivating publishers’ choices but I suspect that librarians (at least in local libraries) are paying more attention to readers’ requests, so this different curatorial attitude may also be reflected in the ratio of “minority” books.