The field of Distributed Ledger Technologies (DLTs) has seen significant advancements, but there is a lack of comprehensive research on the Environmental, Sustainability, and Governance (ESG) aspects of DLT. To address this gap, we conducted a systematic literature review by analyzing a citation network of 63,083 references from 107 seed papers. After refining the corpus to 24,539 publications, we categorized named entities in 46 papers into twelve top-level categories based on an existing technology taxonomy and added DLT’s ESG elements to the taxonomy. Using transformer-based language models, we fine-tuned a pre-trained language model for Named Entity Recognition (NER) using our labeled dataset. This enabled us to distill the corpus to 505 key papers, facilitating a literature review through named entities and temporal graph analysis on the evolution of DLT in the context of ESG. Our contributions include a machine learning-driven methodology for conducting systematic literature reviews in the DLT field, with a focus on ESG aspects. Additionally, we provide a unique NER dataset containing 54,808 named entities, specifically designed for exploring DLT and ESG-related topics.
An NLP Analysis of the Literature: Tracing the Development of ESG-focused DLT Research
