Most of what I've seen about the spectral theory of the graph Laplacian concentrates on $\lambda_2$, the second-smallest eigenvalue. This eigenvalue contains information regarding the connectivity of the graph.
What can one learn from the rest of the eigenvalues and their associated eigenvectors? I'm not interested in special graphs -- e.g. regular graphs -- but large, messy graphs created from data.