Domain Aspect Based Sentiment Analysis

Domain aspect-based sentiment analysis (ABSA) focuses on identifying and classifying sentiments expressed towards specific aspects within text, going beyond general sentiment analysis. Current research heavily emphasizes cross-domain adaptation, aiming to leverage knowledge from data-rich domains to improve performance on data-scarce domains using techniques like contrastive learning, generative models, and in-context learning within various architectures including graph attention networks and pre-trained language models. This fine-grained approach is crucial for applications requiring nuanced understanding of opinions, such as product reviews, social media monitoring, and market research, offering significant improvements over traditional sentiment analysis methods.