mlsanityData to 7 Oct 2026

ECO v1: Towards Event-Centric Opinion Mining

arXiv 2203.12264 ↗First posted 23 Mar 2022cs.CLcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 56 references that are in the map. First posted on arXiv 23 Mar 2022.

Builds on

7 of 56 references.

References · 7

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Revisiting Pre-Trained Models for Chinese Natural Language Processingcited by 262
  3. 2019Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysiscited by 123
  4. 2021A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysiscited by 61
  5. 2016Machine Comprehension Using Match-LSTM and Answer Pointercited by 47
  6. 2019Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasetscited by 46
  7. 2014Opinion mining of movie reviews at document levelcited by 1

Built on by

Cited by year

Citing papers per year: 2023: 1.

1 paper.