ECO v1: Towards Event-Centric Opinion Mining

被引:0
|
作者
Xu, Ruoxi [1 ,3 ]
Lin, Hongyu [1 ]
Liao, Meng [4 ]
Han, Xianpei [1 ,2 ]
Xu, Jin [4 ]
Tan, Wei [4 ]
Sun, Yingfei [3 ]
Sun, Le [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Software, Chinese Informat Proc Lab, Beijing, Peoples R China
[2] Chinese Acad Sci, State Key Lab Comp Sci, Inst Software, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing, Peoples R China
[4] Tencent Inc, WeChat, Data Qual Team, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
EXPRESSIONS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Events are considered as the fundamental building blocks of the world. Mining event-centric opinions can benefit decision making, people communication, and social good. Unfortunately, there is little literature addressing event-centric opinion mining, although which significantly diverges from the well-studied entity-centric opinion mining in connotation, structure, and expression. In this paper, we propose and formulate the task of event-centric opinion mining based on event-argument structure and expression categorizing theory. We also benchmark this task by constructing a pioneer corpus and designing a two-step benchmark framework. Experiment results show that event-centric opinion mining is feasible and challenging, and the proposed task, dataset, and baselines are beneficial for future studies.
引用
收藏
页码:2743 / 2753
页数:11
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