This paper explores the growing importance of Environmental, Social, and Governance (ESG) criteria in financial assessments and conducts an AI-driven analysis of ESG concepts’ evolution from 1980 to 2022. Focusing on media sources from the United States and the United Kingdom, the study utilizes the Dow Jones News Article dataset for a comprehensive analysis focused on the environmental domain. The research introduces an innovative information extraction technique, transforming extracted data into a knowledge graph. Key findings highlight recent trends in ESG aspects, with a notable emphasis on climate change, renewable energy sources, and biodiversity conservation in the environmental dimension.
Angioni, S., Consoli, S., Dessi, D., Osborne, F., Recupero, D., Salatino, A. (2024). Investigating Environmental, Social, and Governance (ESG) Discussions in News: A Knowledge Graph Analysis Empowered by AI. In Second International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data (SemTech4STLD) co-located with the Extended Semantic Web Conference 2024 (ESWC 2024) (pp.49-60). CEUR-WS.
Investigating Environmental, Social, and Governance (ESG) Discussions in News: A Knowledge Graph Analysis Empowered by AI
Osborne F.;
2024
Abstract
This paper explores the growing importance of Environmental, Social, and Governance (ESG) criteria in financial assessments and conducts an AI-driven analysis of ESG concepts’ evolution from 1980 to 2022. Focusing on media sources from the United States and the United Kingdom, the study utilizes the Dow Jones News Article dataset for a comprehensive analysis focused on the environmental domain. The research introduces an innovative information extraction technique, transforming extracted data into a knowledge graph. Key findings highlight recent trends in ESG aspects, with a notable emphasis on climate change, renewable energy sources, and biodiversity conservation in the environmental dimension.
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