Aspect Based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) aims to identify sentiments expressed towards specific aspects or features within text, going beyond overall sentiment classification. Current research heavily utilizes transformer-based models, often incorporating techniques like graph convolutional networks and attention mechanisms to capture complex relationships between aspects, opinions, and sentiments, addressing challenges like long-range dependencies and handling multi-modal data (text and images). ABSA's detailed insights are valuable for various applications, including customer feedback analysis, market research, and improving product development, driving ongoing advancements in natural language processing and related fields.

Papers