Reading Like a Computer

This course counts as a quantitative (Q) requirement for the Core.

Course description:

How can computers be said to “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 and remote access to documents, archives and libraries. 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 and they will critically engage with the notion of a corpus. 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.

In the F22 term, we will be working with a wide variety of texts: fan fiction, Project Gutenberg, open science journals, science fiction, handwritten archives, pdfs, podcasting in global English accents and transcriptions from NYUAD Arts Center performances.

Previous iterations of this syllabus can be found at wp.nyu.edu/rlac and https://sites.google.com/nyu.edu/rlac and https://sites.google.com/nyu.edu/rlac-f21.

This syllabus is provided as an open educational resource with a CC BY-SA-NC 4.0 International license. If you reuse it, in part or in whole, please cite it.

Suggested Citation:

NYU Abu Dhabi. (2021). CDAD UH-1024Q: Reading Like a Computer course syllabus. Abu Dhabi, UAE: David Joseph Wrisley.