Overview and future prospects of emotion-cause pair extraction

Emotion-Cause Pair Extraction (ECPE) is a crucial task in sentiment analysis, aiming to analyze emotions expressed in text and their underlying causes in a reasonable, correct, and efficient manner. It primarily addresses challenges arising from human-machine dialogue and finds application in big data analysis for processing emotion-related text content. The main objective of ECPE is to extract emotion-cause pairs. Currently, this task is evolving rapidly and can be applied to both single-modal and multimodal scenarios. Its core mission remains focused on extracting, combining, and screening emotion-cause pairs. The primary research question is how to enhance the accuracy of ECPE further. This paper presents a comprehensive review of existing literature, summarizes the current development process of ECPE, and envisions the future direction of this task.