Análise Automática de Satisfação do Consumidor na Plataforma Consumidor.gov

Daniel G Silva, Ugo Dias, Anna Beatriz de Souza Perotto, William Batista Aguiar Motta Betker, Eduardo Rocha da Costa

DOI: 10.14209/sbrt.2022.1570823709

Evento: XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2022)

Keywords:

Abstract

This paper studies the effectiveness of Sentiment Analysis, via the BERTimbau language model, for a consumer complaints dataset from the Consumidor.gov platform. Transfer Learning is employed for the finetuning phase and a manually-labelled test set is designed to evaluate the model. Classification results show a F1-Score of 74% for the "Satisfied" class and 81% for the "Unsatisfied" class.

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