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.

There's a thing in journalism now where news is very often reframed in terms of personal anecdote and-or hot take. In an effort to have something new and clickable to say, we reach for the easiest, closest thing at hand, which is, well, ourselves--our opinions and experiences. I worry about this a lot! I do it (and am doing it right now), and I think it's not always for ill. But in a larger sense it's worth wondering to what degree the larger news feed is being diluted by news stories that are not "content dense."