| Issue |
E3S Web Conf.
Volume 723, 2026
2026 International Conference on Artificial Intelligence in Energy and Infrastructure (AIEI 2026)
|
|
|---|---|---|
| Article Number | 01009 | |
| Number of page(s) | 4 | |
| Section | Artificial Intelligence, Machine Learning & Data Analytics | |
| DOI | https://doi.org/10.1051/e3sconf/202672301009 | |
| Published online | 08 July 2026 | |
Construction of a Feature Dictionary and Optimization of an Artificial Neural Network for ESG Information Classification: A Case Study in Vietnam
1 Faculty of Business Administration, Van Lang University, Ho Chi Minh City, Vietnam e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
2 Institute of Postgraduate Education, Van Lang University, Ho Chi Minh City, Vietnam
3 School of Industrial Management, Ho Chi Minh City University of Technology (HCMUT), VNU-HCM, Ho Chi Minh City, Vietnam. e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
4 Faculty of Accounting & Auditing, Van Lang University, Ho Chi Minh City, Vietnam e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
In the context of the global green transition and Vietnam's commitment to achieving Net Zero by 2050, Environmental, Social, and Governance (ESG) disclosures have become crucial. However, corporate ESG reports in Vietnam often lack quantitative data and transparency. Financial news platforms provide abundant, real-time ESG insights, but processing this massive volume manually is unfeasible. This study pioneers the application of an Artificial Neural Network (ANN) combined with Natural Language Processing (NLP) to automatically classify Vietnamese corporate news into E, S, and G pillars,. Using a dataset of 210 scraped articles, we applied TF-IDF for feature extraction and optimized the ANN's hidden layer through grid search,,. The study successfully established a localized core dictionary of 97 Vietnamese ESG keywords. Performance evaluation showed the Environmental (E) model achieved excellent predictive capacity with 90.48% accuracy and an AUC of 1.000 at 5 hidden nodes,. Although the Social and Governance models exhibited instability due to small test sample sizes, the overall framework demonstrates significant potential. This automated approach provides an objective, real-time screening tool, mitigating “greenwashing” practices, assisting investors in directing green capital, and supporting regulatory bodies in promoting sustainable corporate governance
Key words: ESG classification / Artificial Neuron Network (ANN) / Text mining / Vietnamese financial news / Sustainable investing
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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