Enhancing Event-Level Sentiment Analysis with Structured Arguments

doi:10.1145/3477495.3531784

	Enhancing Event-Level Sentiment Analysis with Structured Arguments
	Zhang, Qi 1; Zhou, Jie 2; Chen, Qin 3; Bai, Qinchun 4; He, Liang 3
	2022
会议名称	45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
会议录名称	ASSOC COMPUTING MACHINERY
页码	1944-1949
会议日期	JUL 11-15, 2022
会议地点	Madrid, SPAIN
出版地	NEW YORK
摘要	Previous studies about event-level sentiment analysis (SA) usually model the event as a topic, a category or target terms, while the structured arguments (e.g., subject, object, time and location) that have potential effects on the sentiment are not well studied. In this paper, we redefine the task as structured event-level SA and propose an End-to-End Event-level Sentiment Analysis (E(3)SA) approach to solve this issue. Specifically, we explicitly extract and model the event structure information for enhancing event-level SA. Extensive experiments demonstrate the great advantages of our proposed approach over the state-of-the-art methods. Noting the lack of the dataset, we also release a large-scale real-world dataset with event arguments and sentiment labelling for promoting more researches(1).
关键词	event-level sentiment analysis structured datasets
DOI	10.1145/3477495.3531784
收录类别	CPCI-S
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000852715902002
原始文献类型	Proceedings Paper
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	http://ir.library.ouchn.edu.cn/handle/39V7QQFX/168841
专题	国家开放大学上海分部
通讯作者	Zhou, Jie
作者单位	1.East China Normal Univ, Sch Comp Sci & Technol, Shanghai Key Lab Multidimens Informat Proc, Shanghai, Peoples R China; 2.Fudan Univ, Sch Comp Sci, Shanghai, Peoples R China; 3.East China Normal Univ, Sch Comp Sci & Technol, Shanghai, Peoples R China; 4.Shanghai Open Univ, Shanghai Engn Res Ctr Open Distance Educ, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Qi,Zhou, Jie,Chen, Qin,et al. Enhancing Event-Level Sentiment Analysis with Structured Arguments[C]. NEW YORK,2022:1944-1949.