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Using natural language processing methods to predict judicial outcomes

Bertalan, Vithor Gomes Ferreira

Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto 2020-11-06

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  • Título:
    Using natural language processing methods to predict judicial outcomes
  • Autor: Bertalan, Vithor Gomes Ferreira
  • Orientador: Ruiz, Evandro Eduardo Seron
  • Assuntos: Classificador Jurídico; Predição Jurídica; Processamento De Linguagem Natural; Legal Classifier; Legal Prediction; Natural Language Processing
  • Notas: Dissertação (Mestrado)
  • Descrição: Natural Language Processing (NLP) and Artificial Intelligence (AI) for the field of Law is a growing area, with the potential of radically changing the daily routine of legal professionals. The amount of text generated by those professionals is outstanding, and to this point, it is a knowledge area to be more explored by Computer Science. One of the most acclaimed fields for the combined area of NLP, AI, and Law is Legal Prediction, in which intelligent systems try to predict specific judicial characteristics, such as the judicial outcome or the judicial class or a given case. This research creates classifiers to predict judicial outcomes in the Brazilian legal system. For this purpose, we developed a text crawler to extract data from the official Brazilian electronic legal systems. Afterward, we developed a dataset of Second Degree Murder and Active Corruption cases, and different classifiers, such as Support Vector Machines and Neural Networks, were used to predict judicial outcomes by analyzing textual features. As a final goal, we used the findings of one of the algorithms, Hierarchical Attention Networks, to find a sample of the most important words used to absolve or convict defendants.
  • DOI: 10.11606/D.59.2020.tde-04012021-232455
  • Editor: Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto
  • Data de criação/publicação: 2020-11-06
  • Formato: Adobe PDF
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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