Robust Ranking of Brazilian Supreme Court Decisions

Abstract

This work studies quantitative measures for ranking judicial decisions by the Brazilian Supreme Court (STF). The measures are based on a network built over decisions whose cases were finalized in the Brazilian Supreme Court between 01/2001 and 12/2019, obtained by crawling publicly available STF records. Three ranking measures are proposed; two are adaptations of the PageRank algorithm, and one adapts Kleinberg’s Algorithm. All are compared with respect to agreement on top 100 rankings; we also analyze each measure robustness based on self-agreement under perturbation. We conclude that all algorithms show the network of citations is highly robust under perturbation. Both versions of PageRank, even if producing different rankings, achieved robustness results which are indistinguishable via statistical tests; Kleinberg’s algorithm achieves more promising results to rank leading cases at the top, but it does need more research to achieve this goal.