In recent years, the significance of Environmental, Social, and Governance criteria in assessing financial investments has grown significantly. This paper presents an AI-driven analysis of ESG concepts and their evolution from 1980 to 2022, with a specific focus on media sources from the United States and the United Kingdom. The primary data source utilized is the Dow Jones News Article dataset, providing a comprehensive and high-quality collection of news articles. The study introduces a novel technique for information extraction from news articles, involving the structuring of extracted data into a knowledge graph. The findings identified key trends associated with ESG aspects emerging in recent years. In the environmental dimension, we identified a pronounced emphasis on climate change, renewable energy sources, and biodiversity conservation. Within the social aspect, the analysis pointed out the increasing significance of issues such as racism, gender identity, and human rights, as well as the increasing role of charities, and the ethical challenges of modern supply chains. Finally, in the governance domain, the findings emphasized issues related to corporate governance accountability, workplace ethics, and the conduct and remuneration of executives.

Angioni, S., Consoli, S., Dessi, D., Osborne, F., Recupero, D., Salatino, A. (2024). Exploring Environmental, Social, and Governance (ESG) Discourse in News: An AI-Powered Investigation through Knowledge Graph Analysis. IEEE ACCESS, 12, 77269-77283 [10.1109/ACCESS.2024.3407188].

Exploring Environmental, Social, and Governance (ESG) Discourse in News: An AI-Powered Investigation through Knowledge Graph Analysis

Osborne F.;
2024

Abstract

In recent years, the significance of Environmental, Social, and Governance criteria in assessing financial investments has grown significantly. This paper presents an AI-driven analysis of ESG concepts and their evolution from 1980 to 2022, with a specific focus on media sources from the United States and the United Kingdom. The primary data source utilized is the Dow Jones News Article dataset, providing a comprehensive and high-quality collection of news articles. The study introduces a novel technique for information extraction from news articles, involving the structuring of extracted data into a knowledge graph. The findings identified key trends associated with ESG aspects emerging in recent years. In the environmental dimension, we identified a pronounced emphasis on climate change, renewable energy sources, and biodiversity conservation. Within the social aspect, the analysis pointed out the increasing significance of issues such as racism, gender identity, and human rights, as well as the increasing role of charities, and the ethical challenges of modern supply chains. Finally, in the governance domain, the findings emphasized issues related to corporate governance accountability, workplace ethics, and the conduct and remuneration of executives.
Articolo in rivista - Articolo scientifico
Climate change; Data mining; Environmental monitoring; ESG; Ethics; Extraction Pipeline; Financial management; Government; Knowledge Graph; Knowledge graphs; Monitoring; Monitoring Tool; Reliability; Social factors; Syntactics; Taxonomy;
English
30-mag-2024
2024
12
77269
77283
open
Angioni, S., Consoli, S., Dessi, D., Osborne, F., Recupero, D., Salatino, A. (2024). Exploring Environmental, Social, and Governance (ESG) Discourse in News: An AI-Powered Investigation through Knowledge Graph Analysis. IEEE ACCESS, 12, 77269-77283 [10.1109/ACCESS.2024.3407188].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/485179
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