This is a project by @emilyinamillion that utilizes topic modeling with Non Negative Matrix factorization (python) and has an accompanying D3.js visualization.
If you came here for the topic modeling, one of my ipython notebooks walks through the other algorithms I tried as well as my reasoning for why I settled on NMF.
If you came here for the D3.js, the visualization folder is the entire contents of the live D3.js visualization currently available on Bl.ocks. The visualization lives here.
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Quickstart
# Create the conda environment from the file
conda env create -f environment.yml
# Activate the environment
conda activate supreme-court-topics
# Download required NLTK data and spaCy model
python -c "import nltk; nltk.download('stopwords'); nltk.download('names')"
python -m spacy download en_core_web_sm