Artículo

Unleashing the Potential of Blockchain and Machine Learning: Insights and Emerging Trends From Bibliometric Analysis

Resumen

Blockchain and machine learning (ML) has garnered growing interest as cutting-edge technologies that have witnessed tremendous strides in their respective domains. Blockchain technology provides a decentralized and immutable ledger, enabling secure and transparent transactions without intermediaries. Alternatively, ML is a sub-field of artificial intelligence (AI) that empowers systems to enhance their performance by learning from data. The integration of these data-driven paradigms holds the potential to reinforce data privacy and security, improve data analysis accuracy, and automate complex processes. The confluence of blockchain and ML has sparked increasing interest among scholars and researchers. Therefore, a bibliometric analysis is carried out to investigate the key focus areas, hotspots, potential prospects, and dynamical aspects of the field. This paper evaluates 700 manuscripts drawn from the Web of Science (WoS) core collection database, spanning from 2017 to 2022. The analysis is conducted using advanced bibliometric tools (e.g., Bibliometrix R, VOSviewer, and CiteSpace) to assess various aspects of the research area regarding publication productivity, influential articles, prolific authors, the productivity of academic countries and institutions, as well as the intellectual structure in terms of hot topics and emerging trends. The findings suggest that upcoming research should focus on blockchain technology, AI-powered 5G networks, industrial cyber-physical systems, IoT environments, and autonomous vehicles. This paper provides a valuable foundation for both academic scholars and practitioners as they contemplate future projects on the integration of blockchain and ML.
Akrami, Nouhaila El (58506906000); Hanine, Mohamed (57219370936); Flores, Emmanuel Soriano (57743061600); Aray, Daniel Gavilanes (58171833800); Ashraf, Imran (57195478761)
Unleashing the Potential of Blockchain and Machine Learning: Insights and Emerging Trends From Bibliometric Analysis
2023
10.1109/ACCESS.2023.3298371
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165866619&doi=10.1109%2fACCESS.2023.3298371&partnerID=40&md5=332ca071cf8a184801210e62466ab29c
Chouaib Doukkali University, Laboratory of Information Technologies, National School of Applied Sciences, El Jadida, 24002, Morocco; Universidad Europea Del Atlántico, Santander, 39011, Spain; Universidad Internacional Iberoamericana, Campeche, 24560, Mexico; Universidad Internacional Iberoamericana, Arecibo, 00613, PR, United States; Universidade Internacional Do Cuanza, Bie, Kuito, Angola; Fundación Universitaria Internacional de Colombia, Bogotá, 111311, Colombia; Yeungnam University, Department of Information and Communication Engineering, Gyeongsan, 38541, South Korea
All Open Access; Gold Open Access
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