@inproceedings{campos-etal-2026-structured,
title = "Structured Sentiment Analysis in {B}razilian {P}ortuguese: An Exploratory Study Using {BERT}imbau",
author = "Campos, Andrew B. and
Corr{\^e}a, Ulisses B. and
Freitas, Larissa A. de",
editor = "Souza, Marlo and
de-Dios-Flores, Iria and
Santos, Diana and
Freitas, Larissa and
Souza, Jackson Wilke da Cruz and
Ribeiro, Eug{\'e}nio",
booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 1",
month = apr,
year = "2026",
address = "Salvador, Brazil",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.propor-1.92/",
pages = "927--932",
ISBN = "979-8-89176-387-6",
abstract = "Structured Sentiment Analysis (SSA) aims to extract fine-grained opinion structures as tuples (holder, target, expression, polarity). While recent advances have improved SSA for English, Brazilian Portuguese lacks dedicated resources. This paper presents an exploratory study introducing a manually annotated dataset of hotel reviews for SSA in Brazilian Portuguese. We propose a baseline approach fine-tuning the BERTimbau model under a BIO tagging scheme to extract sentiment spans. Unlike traditional approaches that model relations explicitly, we assess the viability of span-level extraction as a first step for SSA in this language. Experimental results using a strict train/validation/test split show that our approach achieves a span-level F1-score of 48.41 for holder extraction and a macro F1-score of 61.52. We also discuss the linguistic challenges of holder extraction in Portuguese, specifically regarding implicit subjects (pro-drop), and provide a detailed error analysis. These results establish a preliminary baseline for future relation-aware models in Portuguese."
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%0 Conference Proceedings
%T Structured Sentiment Analysis in Brazilian Portuguese: An Exploratory Study Using BERTimbau
%A Campos, Andrew B.
%A Corrêa, Ulisses B.
%A Freitas, Larissa A. de
%Y Souza, Marlo
%Y de-Dios-Flores, Iria
%Y Santos, Diana
%Y Freitas, Larissa
%Y Souza, Jackson Wilke da Cruz
%Y Ribeiro, Eugénio
%S Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1
%D 2026
%8 April
%I Association for Computational Linguistics
%C Salvador, Brazil
%@ 979-8-89176-387-6
%F campos-etal-2026-structured
%X Structured Sentiment Analysis (SSA) aims to extract fine-grained opinion structures as tuples (holder, target, expression, polarity). While recent advances have improved SSA for English, Brazilian Portuguese lacks dedicated resources. This paper presents an exploratory study introducing a manually annotated dataset of hotel reviews for SSA in Brazilian Portuguese. We propose a baseline approach fine-tuning the BERTimbau model under a BIO tagging scheme to extract sentiment spans. Unlike traditional approaches that model relations explicitly, we assess the viability of span-level extraction as a first step for SSA in this language. Experimental results using a strict train/validation/test split show that our approach achieves a span-level F1-score of 48.41 for holder extraction and a macro F1-score of 61.52. We also discuss the linguistic challenges of holder extraction in Portuguese, specifically regarding implicit subjects (pro-drop), and provide a detailed error analysis. These results establish a preliminary baseline for future relation-aware models in Portuguese.
%U https://aclanthology.org/2026.propor-1.92/
%P 927-932
Markdown (Informal)
[Structured Sentiment Analysis in Brazilian Portuguese: An Exploratory Study Using BERTimbau](https://aclanthology.org/2026.propor-1.92/) (Campos et al., PROPOR 2026)
ACL