READING LIKE A COMPUTER
NYU Abu Dhabi
Core competency: Data & Discovery
Faculty: David Joseph Wrisley
Offered: Spring 2018 (next offering 2019-20 academic year)
Number of credits: 4
Pre-requisites or co-requisites: none
Cross listed as CADT, as well as IM and LitCW electives
Short Course description:
How do computers “read” text, and how can computer-assisted analysis of texts give us new access to information about ourselves and the cultural legacies we have inherited? This course explores quantitative methods for discovering and analyzing diverse texts of the human record. It also offers a glimpse into possible futures of reading. Students will both discuss, and put into practice, forms of computer-assisted textual analysis that have revolutionized research in humanities and social science fields in recent years. They will also take a critical look at the “ubiquitous analytics” and the “ubiquitous virtuality” of everyday life. By engaging with the idea of data in the humanities, the course encourages students to reconsider our common-place assumptions about how reading works. Course materials, discussions, and classroom exercises will push students to examine how basic ideas about a text such as author, subject, setting, character or even style might look different when a non-human is involved in the interpretation. The course assumes no prior computer or coding skills, but a willingness to explore new technologies is essential for success.
I anticipate teaching this course again in the 2019-20 academic year. Building on student interest, to the segments on text mining (Voyant and R) and stylometry, I will add a unit on sentiment analysis. Furthermore, I will explore building in a segment on writing for the digital humanities using computational notebooks.