ECO v1: Towards Event-Centric Opinion Mining

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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.

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APA

Xu, R., Lin, H., Liao, M., Han, X., Xu, J., Tan, W., … Sun, L. (2022). ECO v1: Towards Event-Centric Opinion Mining. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 2743–2753). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.findings-acl.216

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