User Review

User review analysis focuses on extracting valuable information from user-generated text to improve various applications, primarily recommender systems and product development. Current research emphasizes personalized review ranking using techniques like contrastive learning and graph neural networks, as well as developing interpretable models to understand the underlying factors driving user sentiment and preferences, often employing transformer-based architectures and latent class modeling. This field significantly impacts businesses by enabling improved product design, targeted advertising, and enhanced customer experience through more effective recommender systems and sentiment monitoring.