FinNLP-KDF@LREC-COLING 2024 Shared Task ML-ESG 3 (ML-ESG 2024)

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@IJCAI-2023 shared 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. The system needs to be aware of the ESG issues of each article. We used multilingual news articles as the raw material, and conduct annotation on the articles. The target languages include English, Chinese, Japanese, and French. Note that, in the Chinese dataset, we merge issues in SASB Standard into MSCI guidelines. In ML-ESG-2, we introduced a new task to continue the discussion on ESG rating. The task we proposed is ESG impact type identification. That is, the models need to identify the given news is an opportunity or risk from the ESG aspect.