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Text Mining as Historical Method

HIST 3368 (undergrad) / Hist 6322 (Grad)

Meets 3:00-3:50PM CT MWF

Meetings will be partly synchronous (via Zoom), partly asynchronous (via Canvas discussion boards, etc.).

About the Course

Computer-powered methods are changing the way that we access information about society. New methods help us to detect change over time, to identify influential figures, and to name turning points. What happens when we apply these tools to a million congressional debates or tweets? This course -- which is appropriate to both computationalists as well as those with a background in the humanities (but not code) -- will teach students how to analyze texts and as data for evidence of change over time. This course is an introduction to the cutting-edge methodologies of textual analysis that are transforming the humanities today.

About the GitHub Repository

The purpose of this repository is to provide resources for digital-history. It aggregates original Notebooks written by Jo Guldi or her research assistant, Steph Buongiorno, Notebooks written by Southern Methodist University's "Data Team" (Rob Kalescky and Eric Godat), and Notebooks written by scholars in the digital humanities. Authorial credit for copied/forked Notebooks is given in associated README.md files located in the Notebook's parent directory. All code copied/forked from others' repositories are subject to the author's original licensing, not the licensing of the present repository.

Initial Clone

git clone https://github.com/stephbuon/digital-history.git --recursive

Subsequent Updates

From inside digital-history directory:

git reset --hard
git pull
git submodule update --recursive 

Setting Up our M2 Environment for the First Time

Log onto M2 and Load JupyterLab

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