ECO v1: Towards Event-Centric Opinion Mining

• URL: http://arxiv.org/abs/2203.12264v1
• Date: Wed, 23 Mar 2022 08:20:45 GMT
• Title: ECO v1: Towards Event-Centric Opinion Mining
• Authors: Ruoxi Xu, Hongyu Lin, Meng Liao, Xianpei Han, Jin Xu, Wei Tan, Yingfei Sun, Le Sun
• Abstract summary: We propose and formulate the task of event-centric opinion mining based on event-argument structure and expression categorizing theory. Experiment results show that event-centric opinion mining is feasible and challenging.
• Score: 35.74022686478367
• License: http://creativecommons.org/licenses/by/4.0/
• 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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