Sentiment Expression

Sentiment expression analysis focuses on automatically identifying and interpreting the sentiment conveyed in text, encompassing both explicit and implicit expressions across various granularities (e.g., sentence, entity, aspect). Current research emphasizes improving the accuracy of sentiment extraction, particularly in complex sentences and multimodal contexts (including images and stickers), often employing large language models fine-tuned via techniques like contrastive learning and reinforcement learning. These advancements have significant implications for applications such as opinion mining, customer feedback analysis, and enhancing human-computer interaction by enabling more nuanced understanding of user sentiment.