Berkeley DLab Python Intensive May 23-26
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01-Intro to NLTK
02-Geographic Imagination
03-Literary Patterns (Probably)
04-Operationalizing
Readings
README.md

README.md

In its most ambitious formulation, the digital humanities aims to articulate new research questions made available by modern computers and data methods. However, it is not immediately obvious how these fit into our existing research projects. How can we leverage programming and statistics toward the kinds of problems that are central to the humanities? Are the findings that result from the much-touted distant reading compatible with those of close reading?

This workshop will take a research-oriented approach to computational text analysis. Each session will explore a published literary study that has used computational evidence along with close reading. Specifically, we will look at code and practice exercises that reproduce the researchers' method or main finding, while building proficiency with common text analysis methods.

The workshop assumes no prior coding experience and will begin with installation of the Python 3.5 programming language through the Anaconda platform.

Readings will be made available but are not required.

This workshop is co-sponsored by Digital Humanities @ Berkeley