Information Mining and Visualization of Data from the Brazilian Supreme Court (STF): A Case Study

F. Coelho, Daniel Chada, P. Cerdeira
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引用次数: 1

Abstract

This paper describes a joint research of the Law School (Direito Rio) and the Applied Math School (EMAp) of the Getulio Vargas Foundation (FGV), Brazil to analyze information from judicial activities in some of the Brazilian courts. The data for the study included the entire collection of judicial decisions from 1988 to the present. The idea was to identify bottlenecks in the judicial processes at the STF. Introduction Large collections of textual data present a substantial challenge for extraction of relevant bits of information to feed subsequent statistical analysis and visualization pipelines. The peculiarities of the knowledge domain often require the implementation of customized natural language processing pipelines, along with specific knowledge organization systems, to describe the relevant terminology. This paper describes a joint research made by the Law School (Direito Rio) and the Applied Math School (EMAp) of the Getulio Vargas Foundation (FGV), Brazil. After initial contacts a joint venture was established between researchers from EMAp and Direito Rio to analyze the information from judicial activities, in some of the Brazilian courts. Initially, the Law School intended to analyze the behavior of the Brazilian Supreme Court (STF) to support public policy-making, and to identify bottlenecks in the judicial processes at the STF. The task was to analyze the texts of the entire set of recorded judicial decisions, accessible through the STF institutional site. This data had never been analyzed on this scale before, so a great deal of exploratory analyses was expected in order to reveal hidden patterns in the data. A number of a priori questions were proposed, basically aimed at determining if the STF was performing according to its constitutionally defined role, and if not, in what way it could be changed to better serve its purpose. Some of the methodology described herein was applied to the generation of the results published in the project‟s first technical report (“I Relatório – abril/2011 – O Múltiplo Supremo”, 2011). The results presented here go more in the general direction of exploratory data analysis.
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巴西最高法院(STF)数据的信息挖掘和可视化:一个案例研究
本文描述了巴西法学院(Direito Rio)和Getulio Vargas基金会(FGV)的应用数学学院(EMAp)的一项联合研究,以分析巴西一些法院的司法活动信息。这项研究的数据包括从1988年到现在的所有司法判决。这样做的目的是找出特别工作组司法程序中的瓶颈。大量的文本数据对提取相关信息以供后续统计分析和可视化管道提出了重大挑战。知识领域的特性通常需要实现定制的自然语言处理管道,以及特定的知识组织系统,以描述相关术语。本文描述了巴西法学院(Direito Rio)和Getulio Vargas基金会(FGV)的应用数学学院(EMAp)的一项联合研究。在初步接触之后,EMAp和Direito Rio的研究人员成立了一个合资企业,分析巴西一些法院司法活动的信息。最初,法学院打算分析巴西最高法院(STF)的行为,以支持公共决策,并确定STF司法程序中的瓶颈。任务是分析整套司法判决记录的文本,这些文书可通过特别工作组机构网站查阅。这些数据以前从未在这种规模上进行过分析,因此希望进行大量的探索性分析,以揭示数据中隐藏的模式。提出了一些先验的问题,主要目的是确定特别基金是否按照其宪法规定的作用行事,如果不是,可以以何种方式加以改变以更好地服务于其目的。本文所述的一些方法应用于该项目的第一份技术报告(“I Relatório - abril/2011 - O Múltiplo Supremo”,2011)中公布的结果的生成。这里给出的结果更倾向于探索性数据分析的一般方向。
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