#Federalist Papers Analysis

Using Tf-ifd vectorization to quantitatively process text and singular value decomposition for visualization, this project seeks to quantitavely analyze the Federalist Papers between its three authors. Aggregating counts of recurrent high scoring tf-ifd vectors, the vocabulary of each author also allows a qualitative analysis of their political ideologies.

Download txt file from Project Gutenberg here: http://www.gutenberg.org/ebooks/18

Dependencies:

--sci-kit learn

--NLTK

--matplotlib

--pandas

--numpy

Many thanks to the developers for NLTK, sci-kit learn, numpy, and pandas. Also credit to Thomas Hughes for his tutorial on tf-ifd visualization for text analysis (https://github.com/tmhughes81/dap).