Polarity Prediction

Polarity prediction, the task of determining the sentiment (positive, negative, or neutral) expressed in text or other modalities, is a core problem in natural language processing and related fields. Current research emphasizes improving accuracy and efficiency, particularly in low-resource settings, using techniques like graph neural networks to incorporate contextual information and leveraging large language models for both prediction and interpretability. These advancements are crucial for applications ranging from social media monitoring and reputation analysis to understanding customer feedback and improving decision-making in various domains.