面向社会媒体的立场检测研究综述  

Review of research on stance detection in social media

作　　者：赵小兵[1,2,3] 尹召宁 王子豪 张袁硕 陈波 Zhao Xiaobing;Yin Zhaoning;Wang Zihao;Zhang Yuanshuo;Chen Bo(Dept.of Information Engineering,Minzu University of China,Beijing 100081,China;National Language Resource Monitoring&Research Center of Minority Languages,Minzu University of China,Beijing 100081,China;Language Information Security Research Center Institute of National Security MUC,Minzu University of China,Beijing 100081,China)

机构地区：[1]中央民族大学信息工程学院,北京100081 [2]中央民族大学国家语言资源监测与研究民族语言中心,北京100081 [3]中央民族大学国家安全研究院语言信息安全研究中心,北京100081

出　　处：《计算机应用研究》2024年第11期3201-3214,共14页Application Research of Computers

基　　金：国家社会科学基金重大项目(22&ZD035);国家语委资助项目(ZDI145-61)。

摘　　要：随着互联网的不断发展,人们广泛使用微博、推特等社交媒体平台,导致每日涌现出巨量的用户生成内容。针对热点/关注话题,分析这些内容背后用户的态度具有重要意义,可以帮助相关人员决策,因此立场检测任务的目标是根据指定的目标和给定的文本,确定用户对目标的立场(支持/反对/中立)。针对立场检测方面的研究阐述了立场检测任务、应用、相关数据资源和相关方法。在任务方面,除了常规的单/多/跨目标立场检测任务,还梳理了零/少样本立场检测的相关工作;在数据资源方面,对近年来公开的数据资源进行了详细梳理介绍;在方法方面,除了传统机器学习方法、神经网络等方法,还梳理了基于预训练模型的方法。最后对立场检测的发展现状进行了总结阐述,并展望了接下来可能的研究热点。With the continuous development of the Internet,people widely use social media platforms such as Weibo and Twitter,resulting in a huge amount of user generated content every day.It is important to analyze the user’s attitude based on the user generated content for hot/focused topics as it can help relevant stakeholders make informed decisions.Therefore,the goal of the stance detection task is to determine the user’s stance(favor/against/neutral)on the target according to the specified target and the given content.This paper described the stance detection tasks,applications,related data resources and related works.For stance detection tasks,in addition to the previous single/multiple/cross target stance detection tasks,this paper also organized the works related to zero/small sample stance detection.For data resources,this paper gave a detailed introduction to the data resources published in recent years.For stance detection methods,in addition to traditional machine learning methods,neural networks and other methods,this paper also sorted out the methods based on the pre training model.Finally,it summarized the development status of stance detection,and looked forward to the possible research hotspots in the future.

关 键 词：目标 立场 立场检测 零/少样本立场检测 预训练模型 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]