As Distributed Ledger Technologies (DLTs) rapidly evolve, their impacts extend beyond technology, influencing environmental and societal aspects. This evolution has increased publications, making manual literature analysis increasingly challenging. We address this with a Natural Language Processing (NLP)-based systematic literature review method to explore the intersection of Distributed Ledger Technology (DLT) with its Environmental, Social, and Governance (ESG) aspects. Our approach involves building and refining a directed citation network from 107 seed papers to a corpus of 24,539 publications and fine-tuning a transformer-based language model for Named Entity Recognition (NER) on DLT and ESG domains. Applying this model, we distilled the corpus to 505 key publications, enabling an inaugural literature review and temporal graph analysis of DLT's evolution in ESG contexts. Our contributions include an adaptable and scalable NLP-driven systematic literature review methodology and a unique NER dataset of 54,808 entities, tailored for DLT and ESG research. Our inaugural literature review demonstrates their applicability and effectiveness in analyzing DLT's evolution and impacts, proving invaluable for stakeholders in the DLT domain.

翻译：随着分布式账本技术（DLT）的快速发展，其影响已超越技术层面，延伸至环境与社会领域。这一发展导致相关出版物数量激增，使得传统文献分析愈发困难。我们提出一种基于自然语言处理（NLP）的系统性文献综述方法，旨在探索分布式账本技术（DLT）与环境、社会和治理（ESG）议题的交叉领域。该方法首先构建并优化由107篇种子论文组成的定向引文网络，最终形成包含24,539篇出版物的语料库；随后，我们微调基于Transformer的语言模型，用于DLT与ESG领域的命名实体识别（NER）。应用该模型，我们将语料库精简至505篇关键出版物，首次实现了DLT在ESG语境下演化的文献综述与时间演化图谱分析。我们的贡献包括：一套具有可扩展性与适应性的NLP驱动系统性文献综述方法论，以及一个专为DLT与ESG研究定制的独特NER数据集（含54,808个实体）。首次文献综述验证了该方法在分析DLT演化与影响方面的实用性与有效性，为DLT领域利益相关者提供了重要参考。