The problem of ranking a set of objects given some measure of similarity is
one of the most basic in machine learning. Recently Agarwal proposed a method
based on techniques in semi-supervised learning utilizing the graph Laplacian.
In this work we consider a novel application of this technique to ranking
binary choice data and apply it specifically to ranking US Senators by their
ideology.