  The follow up of Representative behavior after elections is imperative for a
democratic Representative system, at the very least to punish betrayal with no
re-election. Our goal was to show how to follow Representatives' and how to
show behavior in real situations and observe trends in political crises
including the onset of game changing political instabilities. We used
correlation and correlation distance matrices of Brazilian Representative votes
during four presidential terms. Re-ordering these matrices with Minimal
Spanning Trees displays the dynamical formation of clusters for the sixteen
year period, which includes one Presidential impeachment. The reordered
matrices, colored by correlation strength and by the parties clearly show the
origin of observed clusters and their evolution over time. When large clusters
provide government support cluster breaks, political instability arises, which
could lead to an impeachment, a trend we observed three years before the
Brazilian President was impeached. We believe this method could be applied to
foresee other political storms.
