论辩挖掘研究综述

Argument Mining Review

[目的/意义]论辩挖掘旨在识别论辩性文本中的论辩结构,从而能够理解结论获得的原因与过程,具有重要的学术和应用价值,近年来在社交媒体内容挖掘、法律辅助判案、决策支持等方面得到了广泛关注,是文本挖掘领域一个新兴研究方向。本文旨在对论辩挖掘的研究与应用现状进行梳理与总结,发掘研究热点,为未来研究提供参考。[方法/过程]在计算语言学会(ACL)数据库和Web of Science数据库中,分别以argument mining、argument structure、argument component为检索词进行检索,结合手工筛选,采集到有关论辩挖掘的文献共220篇,采用精读方式,从论辩模型、论辩挖掘任务和论辩挖掘应用三个方面对当前研究进行了分析与总结。[结果/结论]论辩挖掘的研究才刚刚起步,对社交媒体等简单论辩性文本的研究较多,而对科学论文等复杂论辩性文本的研究较少,未来可从论辩标注方案、论辩成分与关系识别、论辩结构优化三个方面对复杂文本展开研究。

[Purpose/significance]Argument mining can identify the argument structure in argumentative texts,so as to help users to understand the reason and process of drawing a conclusion,and thus has important academic and application value.In recent years,argument mining has obtained great attention in social media content mining,legal assistance judgment,decision support and so on,and become a new research direction in the field of text mining.The purpose of this paper is to sort out and summarize the existing studies and application of argument mining,to discover new research hot spots,and to provide reference for future research.[Method/process]We serched literatures by using the keywords of"argument mining OR argument component OR argument structure OR argumentation mining"from the Web of Science and ACL databases and obtained a total of 220 articles,and then analyzed them from three aspects:argument models,argument mining tasks and argument mining applications by intensive reading and content analysis.[Result/conclusion]The research on argument mining has just started.Existing studies focused more on simple argumentative texts such as social media,and ignored complex argumentative texts such as scientific papers.In future,researchers can focus on the argument mining of complex texts and carry out research from three aspects:argument annotation schemas,the identification of argument components and relationships,and the optimization of argument structures.