文本情感原因自动提取综述

Survey on Automatic Emotion Cause Extraction from Texts

情感原因提取是情感计算领域研究的一个新方向,是一种细粒度的情感分析,其目的是要找出给定文档中触发情感的那部分文本,是对情感的一种追根溯源.情感原因提取涉及到语言学、心理学等相关的领域知识,具有较高的学术研究价值和广泛的应用场景.尽管情感计算的相关研究大多集中在情感识别、情感预测、情感信息抽取等方面,但近些年不少学者已开始深入到情感背后的原因分析与提取上,并产生了较为丰富的成果.从问题定义、任务类别、研究方法、主流数据集、评测指标等多个角度对基于文本的情感原因自动提取的研究成果进行全面回顾和分析,重点对情感原因提取的方法特别是基于深度学习的方法进行了梳理,最后总结了现有情感原因提取工作的不足及其未来所面临的挑战.

Emotion cause extraction(ECE)is a new research direction of affective computing.As a kind of fine-grained sentiment analysis,its purpose is to find out the part of the given document text that triggers the emotion,which is also called tracing to the source of an emotion.ECE has a high academic research value and a wide range of application scenarios in reality,because of its involvement in the fields of linguistics,psychology and other related domains.Recognizing the emotion cause in a document is more useful than just only identifying the emotion.For example,it can help people understand the source of stress and better control their emotions.Although most of the research in affective computing focuses on emotion recognition,emotion prediction and emotional information extraction,many scholars have turned to analyze the causes behind emotions,and have produced rich results in recent years.We make a comprehensive review and analysis of automatic ECE from texts in multiple perspectives,starting from the problem definition and the classification of ECE.Then we review the main methods for ECE especially based on deep learning.After that,the benchmark datasets and the evaluation metrics for ECE task are detailed summarized.Finally,we discuss the deficiency of the existing works on ECE and forecast the future challenges.