Blockchain and Artificial Intelligence: Scientometric Analysis and Visualization

Abstract

Integrating Artificial Intelligence (AI) with Blockchain Technology (BT) is deemed the fourth generation of BT applications (Blockchain 4.0). This generation has gained considerable attention from the research community. Such attention has led to a vast amount of scientific literature. However, a comprehensive quantitative analysis of this literature is still missing. The present study conducts a scientometric analysis to explore and characterize the development track and trends of BT-AI research. Using the Web of Science (WoS) Core Collection database, a total of 2615 peer-reviewed journal articles were identified between 2017–2023 and extracted for analysis, while employing VOSviewer and Biblioshiny as software tools. First, the publication trend was analyzed, and the pivotal articles were identified. Second, the scientific collaboration networks were analyzed and mapped to identify the key researchers, countries, and organizations. Third, the sources’ productivity and citation were analyzed and mapped to identify the dependable sources of information and the best-fit sources for publishing the BT-AI studies. Fourth, the conceptual structure for the BT-AI literature was analyzed and visualized using keywords co-occurrence and keywords thematic evolution to explore and identify the research hotspots and emerging themes. The findings of this study can help in further familiarizing new researchers with BT-AI literature and assist practitioners, policy-makers, and editors to focus on the promising and arising BT-AI trends for further development.

Keywords

• Artificial intelligence
• bibliometrics
• blockchains
• data visualization
• reviews