Multi-Lingual ESG Issue Identification (ML-ESG)

Shared Task

Introduction

In FinNLP-2022, we proposed a FinSim4-ESG shared task, which is related to the topic of environmental, social, and corporate governance (ESG). To continue exploring ESG topics, FinNLP-2023 shares a new dataset for the FinNLP community to explore the multi-lingual ESG issue identification task. Based on the MSCI ESG rating guidelines, ESG-related news can be classified into 35 ESG key issues. Thus, the challenge in the proposed task is ESG issue identification. The system needs to be aware of the ESG issues of each article. We use multilingual news articles as the raw material, and conduct annotation on the articles. The target languages include English, Chinese, and French. Note that, in Chinese dataset, we merge issues in SASB Standard into MSCI guidelines

The overview of this shared task series (Chinese) can be found in [1]. 

[1] Yu-Min Tseng, Chung-Chi Chen, Hen-Hsen Huang, and Hsin-Hsi Chen. 2023. DynamicESG: A Dataset for Dynamically Unearthing ESG Ratings from News Articles. In Proceedings of The 32nd ACM International Conference on Information and Knowledge Management (CIKM'23).

Important Dates: Time zone: Anywhere On Earth (AOE)

Policies

Leaderboard

2023 ML-ESG Leaderboard

Shared Task Organizers