Exploring BERT for Aspect-based Sentiment Analysis in Portuguese Language
Keywords:Aspect-Based Sentiment Analysis, BERT, Portuguese Language, Aspect Sentiment Classification
Aspect-Based Sentiment Analysis (ABSA) is a Natural Language Processing (NLP) task that extracts referred aspects from text and assigns polarities to opinions about those aspects. Most research on ABSA focuses on English. Only a few ABSA works deal with the Portuguese language. In this work, we used BERTimbau to create a Question-Answer approach to ABSA in Portuguese. First, we post-trained this model with text from the same domain as our target corpus. Then, we constructed an auxiliary sentence from the aspect and converted ABSA to a sentence-pair classification task, such as question answering (QA) and natural language inference (NLI). Our experiments show that ABSA based on BERT for Portuguese achieved Balanced Accuracy (BACC) of 77% on a corpus of reviews about the accommodation sector using a post-trained model with QA approach.
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Copyright (c) 2022 Émerson Philippe Lopes, Larissa Freitas, Gabriel Gomes, Gerônimo Lemos, Luiz Otávio Hammes, Ulisses B. Corrêa
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.