Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches
This work addresses sentiment analysis for Portuguese text, but it is incremental as it applies existing ensemble methods to a specific language and dataset.
The paper tackled aspect-based sentiment analysis in Portuguese by developing ensemble transformer systems, achieving new state-of-the-art results on both aspect term extraction and sentiment orientation extraction subtasks.
Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks.