Departamento de Física, Universidade Federal do Ceará, Fortaleza, Ceará, Brasil.
Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza, Spain.
PLoS One. 2020 Feb 5;15(2):e0226504. doi: 10.1371/journal.pone.0226504. eCollection 2020.
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.
代表选举后的代表性行为的跟踪对于民主代表制度来说是必要的，至少可以通过不连任来惩罚背叛。我们的目标是展示如何跟踪代表以及如何在实际情况下表现行为，并观察包括游戏规则改变的政治不稳定的出现在内的政治危机的趋势。我们使用了巴西代表在四个总统任期内的投票相关和相关距离矩阵。用最小生成树对这些矩阵进行重新排序，可以显示十六年期间集群的动态形成过程，其中包括一次总统弹劾。重新排序的矩阵，按相关性强度和党派颜色显示，清楚地显示了观察到的集群的起源及其随时间的演变。当大集群提供政府支持集群破裂时，就会出现政治不稳定，这可能导致弹劾，我们在巴西总统被弹劾前三年就观察到了这一趋势。我们相信这种方法可以应用于预测其他政治风暴。
