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Evolution of ESG-focused DLT Research: An NLP Analysis of the Literature

August 23, 2023

Distributed Ledger Technologies (DLTs) have rapidly evolved, necessitating comprehensive insights into their diverse components. However, a systematic literature review that emphasizes the Environmental, Sustainability, and Governance (ESG) components of DLT remains lacking. To bridge this gap, we selected 107 seed papers to build a citation network of 63,083 references and refined it to a corpus of 24,539 publications for analysis. Then, we labeled the named entities in 46 papers according to twelve top-level categories derived from an established technology taxonomy and enhanced the taxonomy by pinpointing DLT's ESG elements. Leveraging transformer-based language models, we fine-tuned a pre-trained language model for a Named Entity Recognition (NER) task using our labeled dataset. We used our fine-tuned language model to distill the corpus to 505 key papers, facilitating a literature review via named entities and temporal graph analysis on DLT evolution in the context of ESG. Our contributions are a methodology to conduct a machine learning-driven systematic literature review in the DLT field, placing a special emphasis on ESG aspects. Furthermore, we present a first-of-its-kind NER dataset, composed of 54,808 named entities, designed for DLT and ESG-related explorations.

Walter Hernandez

University College London & DLT Science Foundation

Kamil Tylinski

DLT Science Foundation & University College London

Editha Nemsic

Mishcon de Reya LLP

Jiangbo Shangguan

HSBC Business School, Peking University, United Kingdom

Alastair Moore

University College London, United Kingdom

Niall Roche

University College London

Nikhil Vadgama

DLT Science Foundation & University College London

Horst Treiblmaier

Modul University Vienna

Paolo Tasca

University College London & DLT Science Foundation

Jiahua Xu

University College London & DLT Science Foundation

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