@inproceedings{xu-etal-2022-eco,
title = "{ECO} v1: Towards Event-Centric Opinion Mining",
author = "Xu, Ruoxi and
Lin, Hongyu and
Liao, Meng and
Han, Xianpei and
Xu, Jin and
Tan, Wei and
Sun, Yingfei and
Sun, Le",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2022",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-acl.216",
doi = "10.18653/v1/2022.findings-acl.216",
pages = "2743--2753",
abstract = "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.",
}
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<abstract>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.</abstract>
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%0 Conference Proceedings
%T ECO v1: Towards Event-Centric Opinion Mining
%A Xu, Ruoxi
%A Lin, Hongyu
%A Liao, Meng
%A Han, Xianpei
%A Xu, Jin
%A Tan, Wei
%A Sun, Yingfei
%A Sun, Le
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Findings of the Association for Computational Linguistics: ACL 2022
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F xu-etal-2022-eco
%X 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.
%R 10.18653/v1/2022.findings-acl.216
%U https://aclanthology.org/2022.findings-acl.216
%U https://doi.org/10.18653/v1/2022.findings-acl.216
%P 2743-2753
Markdown (Informal)
[ECO v1: Towards Event-Centric Opinion Mining](https://aclanthology.org/2022.findings-acl.216) (Xu et al., Findings 2022)
ACL
- Ruoxi Xu, Hongyu Lin, Meng Liao, Xianpei Han, Jin Xu, Wei Tan, Yingfei Sun, and Le Sun. 2022. ECO v1: Towards Event-Centric Opinion Mining. In Findings of the Association for Computational Linguistics: ACL 2022, pages 2743–2753, Dublin, Ireland. Association for Computational Linguistics.