Data Mining in Environmental, Social, Governance (ESG) Analysis: An Overview
Ali Fuseini *
Computer Science Department, Takoradi Technical University, Ghana.
Nana Kweku Nkyekyer
Computer Science Department, Takoradi Technical University, Ghana.
Kelvin Kojo Bennin
Computer Science Department, Takoradi Technical University, Ghana.
Richard Essah
Computer Science Department, Takoradi Technical University, Ghana.
*Author to whom correspondence should be addressed.
Abstract
ESG (environmental, social, and governance) considerations are now essential standards for evaluating the ethical and sustainable effects of investments. This study examines data mining's use in ESG analysis, emphasizing how it may be used to glean useful insights from sizable and varied datasets. It looks at data mining techniques, resources, and applications for trend identification, ESG compliance assessment, and decision support. Future directions, ethical issues, and difficulties in incorporating cutting-edge technologies into ESG analysis are also covered.
Keywords: ESG analysis, data mining, sustainability, environmental performance, social equity, governance transparency, machine learning, text mining, clustering algorithms, predictive, predictive modeling, sentiment analysis, big data, standardization of ESG metrics, real-time ESG monitoring, IOT in ESG, blockchain for governance, ESG reporting, sustainable investments, anomaly detection, greenwashing