Critical Digital Humanities: Notes and Code

The following are all Jupyter Python notebooks that either demonstrate methods and techinques or provide commentary in the form of evaluation or verification of computational criticism / digital humanities methods.

Using the HATHI Trust Extracted Features datasets for training word2vec models using Doc2Vec. [Viewer] [Download]
Python (using Scikit-Learn and NLTK) version of Andrew Piper's MDS plotting of Augustine's Confessions. [Viewer][Download]
Evaluating Eucidean distance metric/Cosine Similarity and MDS as index/correlate of "conversion" in Frederick Douglass's Narrative of the Life of Frederick Douglass. [Notebook]
Interpreting Computational Models: Examining Contribution to Distance Metrics. [Notebook]