Machine Learning–Based Classification of ESG News: Environmental Information from Digital Media in Vietnam
機械学習に基づくESGニュース分類：ベトナムのデジタルメディアからの環境情報 (AI 翻訳)
Anh Bui-Tuyet, Anh Nguyen-Ngoc-Lan, Nhu Hung Duong, Van Nguyen-Thi-Thu
🤖 gxceed AI 要約
日本語
ベトナムのESG開示は断片的で報告書ベースのデータが乏しい。本研究は、機械学習パイプラインによりベトナムESGニュースの環境(E)柱を分類し、ChatGPTベースの解釈性エージェント「ClearESG-E」でGRIフレームワークにマッピングする。手動ラベル付きコーパスでベンチマークし、外部検証で汎化性能を確認。低リソース環境における透明なESGモニタリングに貢献。
English
Vietnam's ESG disclosure is fragmented and report-based data scarce. This study develops an ML pipeline to classify Vietnamese ESG news on the environmental pillar and maps each to GRI criteria via a ChatGPT-based interpretability agent. Benchmarking on a manually labeled corpus and external validation show strong generalization. Contributes to transparent ESG monitoring in emerging markets.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
ベトナムのESG情報開示は自主的枠組みに依存しており、日本企業のベトナム進出・投資判断にも影響する。SSBJや有報でのESG開示が進む日本にとって、新興国での機械学習を用いたリアルタイムESGモニタリング手法は参考になる。
In the global GX context
Vietnam represents a low-resource ESG disclosure environment typical of emerging markets. The ML pipeline demonstrates how digital media can supplement structured ESG data, relevant for global investors and disclosure scholars applying similar methods in other emerging economies.
👥 読者別の含意
🔬研究者:Provides a validated framework for ESG news classification in low-resource languages, useful for comparative studies.
🏢実務担当者:Can be adapted by firms or investors to monitor environmental news in Vietnamese markets.
🏛政策担当者:Shows potential for using AI to enhance ESG oversight in emerging markets without mandatory disclosure.
📄 Abstract（原文）
Vietnam’s ESG disclosure landscape remains fragmented and report-based ESG data is scarce, leaving stakeholders with limited tools to monitor corporate environmental behaviour in near real time. We address this gap by developing an end-to-end pipeline that classifies Vietnamese ESG news on the environmental (E) pillar and links each classification to the Global Reporting Initiative (GRI) framework through a ChatGPT-based interpretability agent (“ClearESG-E”). The pipeline is benchmarked on a manually labelled corpus of news articles covering firms in the Vietnam Sustainability Index (VNSI) and externally validated on a disjoint set of newly labelled articles. The contribution is threefold: a Vietnamese ESG-news classification framework tailored to a low-resource, lexicon-driven setting; an externally validated evidence of generalisation that the top classifiers retain strong discriminative performance on unseen content; and an interpretability layer that maps each environmentally relevant article to GRI sub-criteria with traceable textual evidence, supporting transparent ESG monitoring in emerging markets.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://www.e3s-conferences.org/articles/e3sconf/pdf/2026/41/e3sconf_aiei2026_01003.pdffirst seen 2026-07-13 06:51:44
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