ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation
Researchers have developed ACAT, a novel web-based platform designed to streamline the annotation process for Aspect-Based Sentiment Analysis (ABSA) datasets. ACAT natively supports four distinct ABSA workflows, including aspect-category sentiment analysis and aspect sentiment triplet extraction. A key innovation is its automated ETL pipeline, which consolidates collaborative annotations and calculates Inter-Annotator Agreement (IAA) metrics upon export, producing ready-to-use training datasets. Preliminary testing showed ACAT significantly reduced annotation time and yielded high IAA scores. AI
IMPACT This tool could accelerate the development of more accurate sentiment analysis models by simplifying data annotation.