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.

Highlights

  • The data mining consisted of processing individual files containing the results of the rollcall votes of Deputies for each session over 16 years

  • If the information about the substitute of Deputy was scarce, we assume that substitute was a member of the same political party and if the absence zones and vote zones coincide, the substitute vote is computed

  • The Prim algorithm jth step consists of finding the closest pair of vertices to set of (j − 1)th Minimal Spanning Tree (MST) sub network Nj−1 for each only one vertex, but not the other, belongs to Nj−1

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Summary

Introduction

The data mining consisted of processing individual files containing the results of the rollcall votes of Deputies for each session over 16 years. Special care was taken to account for partial and total absence frequency of a Deputy in each year. The partial absence zones were filled using information about substitutes for each Deputy. Deputies with total absences throughout the year without certified substitute were eliminated.

Results
Conclusion
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