# Time evolution of the behaviour of Brazilian legislative Representatives using a complex network approach

## TL;DR

This study analyzes the evolving voting behavior of Brazilian legislative representatives over sixteen years using complex network methods, revealing patterns that precede political crises like impeachment.

## Contribution

It introduces a novel approach combining correlation matrices and minimal spanning trees to track political behavior and predict instability in legislative systems.

## Key findings

- Clusters in voting behavior correlate with political stability.
- Breaks in government support clusters precede impeachment.
- Method can potentially forecast political crises.

## Abstract

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.