People’s opinions are a great source of information for other people and organizations, public or private. Typically works focused on Portuguese perform Document Level Sentiment Analysis. It is hard to find Aspect-Based Sentiment Analysis (ABSA) approaches or datasets available for Portuguese.

We propose to create an Aspect-Based Sentiment Analysis for TripAdvisor reviews written in Portuguese. Two sub-tasks will be available: Aspect Term Extraction and Sentiment Orientation Extraction. The first task comprehends the identification of aspects into the reviews, and the later task proposes to extract the sentiment orientation (polarity) of the review about a single aspect mentioned on it.

The availability of corpora written in Portuguese is scarce, which limits the amount of research done for this language.

This task will contribute to the progress of Portuguese NLP, as there is a demand in the area for the development of new methods and tools.

Previous Aspect-Based Sentiment Analysis competitions, such as SemEval [3, 4, 5] and EVALITA [6] inspired us to develop a specific task for Portuguese.

The corpora contains travellers' reviews about accomodation services companies, written in Portuguese. In this task, we used corpora developed previously by Freitas [1] and Corrêa [2]. Freitas’ corpus is publicly available, so it will be used only in the training dataset. Corrêa’s corpus is private and will be splitted to training and test datasets. The full dataset will be available after the event.

Both datasets were annotated following the same annotation guidelines [1]. Aspects annotated were the concepts on the Accommodation Services Domain Ontology, HOntology [7].

Participating teams will receive manually annotated training and test datasets. Submissions for the test dataset will be evaluated on several metrics, such as Accuracy, Precision, Recall, F1, and Bacc. The submissions will be ranked according to Acc in task 1 and Bacc in task2.

The expected target is anyone interested in Aspect-Based Sentiment Analysis. We hope for substantial engagement of academics, researchers, students, industrial teams, and practitioners of private companies.

1. L. A. de Freitas. Feature-level sentiment analysis applied to Brazilian Portuguese reviews. PhD thesis, Pontifícia Universidade Católica do Rio Grande do Sul (2015).

2. U. B. Corrêa. Análise de sentimento baseada em aspectos usando aprendizado profundo: uma proposta aplicada à língua portuguesa. PhD thesis, Universidade Federal de Pelotas (2021).

3. M. Pontiki and D. Galanis and J. Pavlopoulos and H. Papageorgiou and I. Androutsopoulos and S. Manandhar. SemEval-2014 Task 4: Aspect Based Sentiment Analysis. In Proceedings of the 8th International Workshop on Semantic Evaluations (SemEval-2014), pages 27–35, Dublin, Ireland, 2014. Association for Computational Linguistics.

4. M. Pontiki and D. Galanis and H. Papageorgiou and S. Manandhar and I. Androutsopoulos. SemEval-2015 Task 12: Aspect Based Sentiment Analysis. In Proceedings of the 9th International Workshop on Semantic Evaluations (SemEval-2015), pages 486-495, Denver, Colorado, USA, 2015. Association for Computational Linguistics.

5. M. Pontiki and D. Galanis and H. Papageorgiou and I. Androutsopoulos and S. Manandhar and M. AL-Smadi and M. Al-Ayyoub and Y. Zhao and B. Qin and O. De Clercq and V. Hoste and M. Apidianaki and X. Tannier and N. Loukachevitch and E. Kotelnikov and N. Bel and S. M. Jiménez-Zafra and G. Eryigit. SemEval-2016 Task 5: Aspect Based Sentiment Analysis. In Proceedings of the 10th International Workshop on Semantic Evaluations (SemEval-2016), pages 19–30, San Diego, California, USA, 2016. Association for Computational Linguistics.

6. L. De Mattei and G. De Martino and A. Lovine and A. Miaschi and M. Polignano and G. Rambelli. Overview of the Aspect Term Extraction and Aspect-based Sentiment Analysis Task. In Proceedings of the 7th Evaluation Campaign of Natural Language Processing and Speech tools for Italian (EVALITA 2020), Online. CEUR.org.

7. M. S. Chaves and L. A. de Freitas and R. Vieira. HOntology: a multilingual ontology for the accommodation sector in the tourism industry. In Proceedings of the 4th International Conference on Knowledge Engineering and Ontology Development (KEOD 2012), pages 149-154, Barcelona, Spain, 2012.