  Signed networks and balance theory provide a natural setting for real-world
scenarios that show polarization dynamics, positive/negative relationships, and
political partisanship. For example, they have been proven effective in
studying the increasing polarization of the votes in the two chambers of the
U.S. Congress from World War II on.
  To provide further insights into this particular case study, we propose the
application of a pipeline to analyze and visualize a signed graph's
configuration based on the exploitation of the corresponding Laplacian matrix'
spectral properties. The overall methodology is comparable with others based on
the frustration index, but it has at least two main advantages: first, it
requires a much lower computational cost; second, it allows for a quantitative
and visual assessment of how arbitrarily small subgraphs (even single nodes)
contribute to the overall balance (or unbalance) of the network.
  The proposed pipeline allows the exploration of polarization dynamics shown
by the U.S. Congress from 1945 to 2020 at different resolution scales. In fact,
we are able to spot and point out the influence of some (groups of) congressmen
in the overall balance, as well as to observe and explore polarization's
evolution of both chambers across the years.
