  A U.S. Senator from South Dakota donated documents that were accumulated
during his service as a house representative and senator to be housed at the
Bridges library at South Dakota State University. This project investigated the
utility of quantitative statistical methods to explore some portions of this
vast document collection. The available scanned documents and emails from
constituents are analyzed using natural language processing methods including
the Latent Dirichlet Allocation (LDA) model. This model identified major topics
being discussed in a given collection of documents. Important events and
popular issues from the Senator Daschles career are reflected in the changing
topics from the model. These quantitative statistical methods provide a summary
of the massive amount of text without requiring significant human effort or
time and can be applied to similar collections.
