Aspect Sentiment

Aspect-based sentiment analysis (ABSA) focuses on identifying the sentiment expressed towards specific aspects or features within a text, going beyond simple positive/negative classification. Current research emphasizes improving accuracy by addressing noise in multimodal data (text and images) and developing models that leverage both local syntactic information and global relationships between words and aspects, often employing graph neural networks and variational autoencoders. This refined understanding of nuanced sentiment has significant implications for various applications, including improved financial analysis through explainable AI and more effective user feedback processing.