Exploring BERT for Aspect Extraction in Portuguese Language

Authors

  • Émerson Lopes Federal University of Pelotas
  • Ulisses Correa IFSul
  • Larissa Freitas Federal University of Pelotas

DOI:

https://doi.org/10.32473/flairs.v34i1.128357

Keywords:

Aspect-Based Sentiment Analysis, Aspect Extraction, BERT, Portuguese Language

Abstract

Sentiment Analysis is the computer science field that comprises techniques that aim to automatically extract opinions from texts. Usually, these techniques assign a Sentiment Orientation to the whole document (Document Level Sentiment Analysis). But a document can express sentiment about several aspects of an entity. Methods that extract those aspects, paired with the sentiment about them, operate in the Aspect Level. Aspect-Based Sentiment Analysis approaches can be split into two stages: Aspect Extraction and Aspect Sentiment Classification. The literature presents works mainly focused on reviews about hotels, smartphones, or restaurants. In this work, we present an approach for Aspect Extraction based on Multilingual (Google's) and Portuguese (BERTimbau) BERT pre-trained models. Our experiments show that Aspect Extraction based on BERT pre-trained for Portuguese achieved Balanced Accuracy of up to 93% on a corpus of reviews about the accommodation sector.

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Published

2021-04-18

How to Cite

Lopes, Émerson, Correa, U., & Freitas, L. (2021). Exploring BERT for Aspect Extraction in Portuguese Language. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128357

Issue

Section

Special Track: Applied Natural Language Processing