IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i19p3119-d1492705.html
   My bibliography  Save this article

Understanding Public Opinion towards ESG and Green Finance with the Use of Explainable Artificial Intelligence

Author

Listed:
  • Wihan van der Heever

    (College of Computing and Data Science, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore)

  • Ranjan Satapathy

    (Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore)

  • Ji Min Park

    (Nanyang Business School, Nanyang Technological University, Gaia, 91 Nanyang Avenue, Singapore 639956, Singapore)

  • Erik Cambria

    (College of Computing and Data Science, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore)

Abstract

This study leverages explainable artificial intelligence (XAI) techniques to analyze public sentiment towards Environmental, Social, and Governance (ESG) factors, climate change, and green finance. It does so by developing a novel multi-task learning framework combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning to extract nuanced insights from a large corpus of social media data. Our approach integrates state-of-the-art models, including the SenticNet API, for sentiment analysis and implements multiple XAI methods such as LIME, SHAP, and Permutation Importance to enhance interpretability. Results reveal predominantly positive sentiment towards environmental topics, with notable variations across ESG categories. The contrastive learning visualization demonstrates clear sentiment clustering while highlighting areas of uncertainty. This research contributes to the field by providing an interpretable, trustworthy AI system for ESG sentiment analysis, offering valuable insights for policymakers and business stakeholders navigating the complex landscape of sustainable finance and climate action. The methodology proposed in this paper advances the current state of AI in ESG and green finance in several ways. By combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning, our approach provides a more comprehensive understanding of public sentiment towards ESG factors than traditional methods. The integration of multiple XAI techniques (LIME, SHAP, and Permutation Importance) offers a transparent view of the subtlety of the model’s decision-making process, which is crucial for building trust in AI-driven ESG assessments. Our approach enables a more accurate representation of public opinion, essential for informed decision-making in sustainable finance. This paper paves the way for more transparent and explainable AI applications in critical domains like ESG.

Suggested Citation

  • Wihan van der Heever & Ranjan Satapathy & Ji Min Park & Erik Cambria, 2024. "Understanding Public Opinion towards ESG and Green Finance with the Use of Explainable Artificial Intelligence," Mathematics, MDPI, vol. 12(19), pages 1-21, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3119-:d:1492705
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/19/3119/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/19/3119/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.
    2. Samuel Drempetic & Christian Klein & Bernhard Zwergel, 2020. "The Influence of Firm Size on the ESG Score: Corporate Sustainability Ratings Under Review," Journal of Business Ethics, Springer, vol. 167(2), pages 333-360, November.
    3. Caroline Flammer & Michael W. Toffel & Kala Viswanathan, 2021. "Shareholder activism and firms' voluntary disclosure of climate change risks," Strategic Management Journal, Wiley Blackwell, vol. 42(10), pages 1850-1879, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vincenzo D'Apice & Giovanni Ferri & Mariantonietta Intonti, 2021. "Sustainable disclosure versus ESG intensity: Is there a cross effect between holding and SRI funds?," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1496-1510, September.
    2. Spira, Robin, 2024. "How does ESG rating disagreement influence analyst forecast dispersion?," Junior Management Science (JUMS), Junior Management Science e. V., vol. 9(3), pages 1769-1804.
    3. Scholz, Robert, 2023. "Unternehmensmitbestimmung und die sozialökologische Transformation: Zusammenhang zwischen Mitbestimmungsindex und ESG-Kriterien in börsennotierten Unternehmen," Mitbestimmungsreport 79, Hans-Böckler-Stiftung, Düsseldorf.
    4. Ting Qian & Caoyuan Yang, 2023. "State-Owned Equity Participation and Corporations’ ESG Performance in China: The Mediating Role of Top Management Incentives," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    5. Jiang, Yihuo & Ni, Hongliang & Ni, Yihan & Guo, Xiaomei, 2023. "Assessing environmental, social, and governance performance and natural resource management policies in China's dual carbon era for a green economy," Resources Policy, Elsevier, vol. 85(PB).
    6. Andreas Wagner & Denise Fischer‐Kreer, 2024. "The role of CEO regulatory focus in increasing or reducing corporate carbon emissions," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 1051-1065, February.
    7. Ariana Chang & Tian‐Shyug Lee & Hsiu‐Mei Lee, 2024. "Applying sustainable development goals in financial forecasting using machine learning techniques," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(3), pages 2277-2289, May.
    8. Liu, Meiling, 2024. "The impact of directors' foreign experience on corporate carbon emissions: A mediating perspective based on corporate green innovation," Finance Research Letters, Elsevier, vol. 62(PB).
    9. Sumin Hu & Qi Zhu & Xia Zhao & Ziyue Xu, 2023. "Digital Finance and Corporate Sustainability Performance: Promoting or Restricting? Evidence from China’s Listed Companies," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    10. Torsten Ehlers & Ulrike Elsenhuber & Kumar Jegarasasingam & Eric Jondeau, 2022. "Deconstructing ESG Scores: How to Invest with Your own Criteria," Swiss Finance Institute Research Paper Series 22-23, Swiss Finance Institute.
    11. Natalia Semenova, 2021. "Management control systems in response to social and environmental risk in large Nordic companies," International Journal of Corporate Social Responsibility, Springer, vol. 6(1), pages 1-11, December.
    12. Tan, Yafei & Zhu, Zhaohui, 2022. "The effect of ESG rating events on corporate green innovation in China: The mediating role of financial constraints and managers' environmental awareness," Technology in Society, Elsevier, vol. 68(C).
    13. Fiorillo, Paolo & Santilli, Gianluca, 2024. "The influence of shareholder ESG performance on corporate sustainability: Exploring the role of ownership structure," Finance Research Letters, Elsevier, vol. 67(PA).
    14. Valeria D’Amato & Rita D’Ecclesia & Susanna Levantesi, 2021. "Fundamental ratios as predictors of ESG scores: a machine learning approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1087-1110, December.
    15. Jonathan Taglialatela & Kevin Pirazzi Maffiola & Roberto Barontini & Francesco Testa, 2023. "Board of Directors' characteristics and environmental SDGs adoption: an international study," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(5), pages 2490-2506, September.
    16. Bauckloh, Michael Tobias & Beyer, Victor & Klein, Christian, 2022. "Does it pay to invest in dirty industries? New insights on the shunned-stock hypothesis," CFR Working Papers 22-07, University of Cologne, Centre for Financial Research (CFR).
    17. Ren, Xiaohang & Zeng, Gudian & Zhao, Yang, 2023. "Digital finance and corporate ESG performance: Empirical evidence from listed companies in China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    18. Finja Lena Kind & Jennifer Zeppenfeld & Rainer Lueg, 2023. "The impact of chief executive officer narcissism on environmental, social, and governance reporting," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4448-4466, November.
    19. Peng, Shengnan & Liu, Chan & Wang, Ze & Ye, Zihan & Sun, Xialing & Tan, Zhanglu, 2024. "The impact of the carbon reduction policy effectiveness on energy companies' ESG performance," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    20. Jun Wan & Yuejia Wang & Yuan Wang, 2025. "Promoting or Hindering: The Impact of ESG Rating Differences on Energy Enterprises’ Green Transformation—A Causal Test from Double Machine-Learning Algorithms," Energies, MDPI, vol. 18(3), pages 1-21, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3119-:d:1492705. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.