Banca de QUALIFICAÇÃO: Ilo César Duarte Cabral

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : Ilo César Duarte Cabral
DATE: 31/01/2023
TIME: 14:00
LOCAL: remoto
TITLE:

Mining of Federal Legislative Data for Analysis and Prediction of Lawmaking

KEY WORDS:
PAGES: 47
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SUMMARY:

The disclosure of legislative data by the Brazilian government opened an opportunity to understand aspects related to the legislative process. Predicting the votes of deliberative bodies, for example, can lead to a better understanding of government policies and thus generate actionable strategies for social good. This work sets out to develop a model for analysis and prediction that maximizes the use of publicly accessible heterogeneous data from legislative data to understand the approval/failure of legislative proposals. In particular, a prediction model will be developed that includes the use of machine learning algorithms and natural language processing to identify discriminative factors that may influence the decision to approve a bill. The studies and investigations that will be carried out in this work should generate results that make it possible to add knowledge and lead to a better understanding of aspects related to the Brazilian legislative process, helping companies and other governmental and non-governmental entities to prioritize controversial bills and to understand patterns wider in the behavior of legislators.

BANKING MEMBERS:
Presidente - 3064724 - GLAUCO VITOR PEDROSA
Interno - 3089262 - JOHN LENON CARDOSO GARDENGHI
Interno - 3128249 - LUIS PAULO FAINA GARCIA
Externo à Instituição - EDUARDO DE PAULA COSTA - USP