UOA at the FinNLP-2022 ERAI Task: Leveraging the Class Label Description for Financial Opinion Mining
Jinan Zou, Haiyao Cao, Yanxi Liu, Lingqiao Liu, Ehsan Abbasnejad, Javen Qinfeng Shi
Abstract
Evaluating the Rationales of Amateur Investors (ERAI) is a task about mining expert-like viewpoints from social media. This paper summarizes our solutions to the ERAI shared task, which is co-located with the FinNLP workshop at EMNLP 2022. There are 2 sub-tasks in ERAI. Sub-task 1 is a pair-wised comparison task, where we propose a BERT-based pre-trained model projecting opinion pairs in a common space for classification. Sub-task 2 is an unsupervised learning task ranking the opinions’ maximal potential profit (MPP) and maximal loss (ML), where our model leverages the regression method and multi-layer perceptron to rank the MPP and ML values. The proposed approaches achieve competitive accuracy of 54.02% on ML Accuracy and 51.72% on MPP Accuracy for pairwise tasks, also 12.35% and -9.39% regression unsupervised ranking task for MPP and ML.- Anthology ID:
- 2022.finnlp-1.15
- Volume:
- Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Chung-Chi Chen, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen
- Venue:
- FinNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 122–126
- Language:
- URL:
- https://aclanthology.org/2022.finnlp-1.15
- DOI:
- 10.18653/v1/2022.finnlp-1.15
- Cite (ACL):
- Jinan Zou, Haiyao Cao, Yanxi Liu, Lingqiao Liu, Ehsan Abbasnejad, and Javen Qinfeng Shi. 2022. UOA at the FinNLP-2022 ERAI Task: Leveraging the Class Label Description for Financial Opinion Mining. In Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP), pages 122–126, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- UOA at the FinNLP-2022 ERAI Task: Leveraging the Class Label Description for Financial Opinion Mining (Zou et al., FinNLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2022.finnlp-1.15.pdf