Overview of the FinNLP-2022 ERAI Task: Evaluating the Rationales of Amateur Investors

Chung-Chi Chen, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen


Abstract
This paper provides an overview of the shared task, Evaluating the Rationales of Amateur Investors (ERAI), in FinNLP-2022 at EMNLP-2022. This shared task aims to sort out investment opinions that would lead to higher profit from social platforms. We obtained 19 registered teams; 9 teams submitted their results for final evaluation, and 8 teams submitted papers to share their methods. The discussed directions are various: prompting, fine-tuning, translation system comparison, and tailor-made neural network architectures. We provide details of the task settings, data statistics, participants’ results, and fine-grained analysis.
Anthology ID:
2022.finnlp-1.11
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:
99–103
Language:
URL:
https://aclanthology.org/2022.finnlp-1.11
DOI:
10.18653/v1/2022.finnlp-1.11
Bibkey:
Cite (ACL):
Chung-Chi Chen, Hen-Hsen Huang, Hiroya Takamura, and Hsin-Hsi Chen. 2022. Overview of the FinNLP-2022 ERAI Task: Evaluating the Rationales of Amateur Investors. In Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP), pages 99–103, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
Overview of the FinNLP-2022 ERAI Task: Evaluating the Rationales of Amateur Investors (Chen et al., FinNLP 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-4/2022.finnlp-1.11.pdf