Scientific knowledge production of blockchain: A bibliometric and lexicometric review
Wilfrid Azan (COACTIS, BETA), Yuan Li (COACTIS)

TL;DR
This paper provides a comprehensive bibliometric and lexicometric analysis of blockchain research, revealing its multidisciplinary nature, evolution, and epistemic boundaries to guide future development.
Contribution
It offers the first combined bibliometric and lexicometric review of blockchain literature, mapping its knowledge evolution and identifying core epistemic communities.
Findings
Blockchain research is multidisciplinary, involving four major disciplines.
The field is maturing with increasing technological infrastructure focus.
Blockchain functions more as a boundary object than a disruptive innovation.
Abstract
While recent reviews of blockchain technology have focused on the latest developments in cryptocurrency and their derivative impacts, less attention has been given to analysing their knowledge paths and boundaries based on past research to guide their development. To address this gap, we conducted both a bibliometric study of 2525 articles and a lexicometric study of 123 articles. The bibliometric study provided holistic insights into the evolution and distribution of blockchain research, including influential researchers and countries, discipline composition, knowledge development trends, and emerging frontiers. The lexicometric study identified the boundary concept structure with a quantitative textual approach, extracting the strongest signifying epistemic communities. Our findings indicate that blockchain research draws from four major disciplines, making it a multidisciplinary…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBlockchain Technology Applications and Security · FinTech, Crowdfunding, Digital Finance · Big Data and Business Intelligence
