Machine Learning and Blockchain: A Bibliometric Study on Security and Privacy

This study examines the factors influencing scientific productivity in blockchain, privacy, and cybersecurity research across countries. While previous research has explored the determinants of general scientific output, less is known about the patterns of influence in these technological fields, which have been dominantly studied with a bibliometric focus. Using regression models, we analyze the impact of economic, political, educational, and social factors on the publication rates in these domains. Data from international databases on country-level indicators and scientific publications form the basis of our analysis. The results show that Gross National Income per capita is the strongest predictor of research output across all the fields studied. Research spending as a percentage of GDP also demonstrates a consistent positive relationship with publication rates. However, the impact of the factors varies across fields. This research provides insights for policymakers and institutions aiming to enhance research capabilities in these critical areas of technology.

show abstract

Technical Innovations and Social Implications: Mapping Global Research Focus in AI, Blockchain, Cybersecurity, and Privacy

Bran,

Rughiniș,

Țurcanu

et al. 2024

Computers

View full text Add to dashboard Cite

This study examines the balance between technical and social focus in artificial intelligence, blockchain, cybersecurity, and privacy publications in Web of Science across countries, exploring the social factors that influence these research priorities. We use regression analysis to identify predictors of research focus and cluster analysis to reveal patterns across countries, combining these methods to provide a broader view of global research priorities. Our findings reveal that liberal democracy index, life expectancy, and happiness are significant predictors of research focus, while traditional indicators like education and income show weaker relationships. This unexpected result challenges conventional assumptions about the drivers of research priorities in digital technologies. The study identifies distinct clusters of countries with similar patterns of research focus across the four technologies, revealing previously unrecognized global typologies. Notably, more democratic societies tend to emphasize social implications of technologies, while some rapidly developing countries focus more on technical aspects. These findings suggest that political and social factors may play a larger role in shaping research agendas than previously thought, necessitating a re-evaluation of how we understand and predict research focus in rapidly evolving technological fields. The study provides valuable information for policymakers and researchers, informing strategies for technological development and international collaboration in an increasingly digital world.

show abstract

Machine Learning and Blockchain: A Bibliometric Study on Security and Privacy

Cited by 4 publications

References 51 publications

Federated Learning Strategies for Privacy-Preserving Machine Learning Models in Cloud Computing Environments

Federated Learning Strategies for Privacy-Preserving Machine Learning Models in Cloud Computing Environments

Decoding National Innovation Capacities: A Comparative Analysis of Publication Patterns in Cybersecurity, Privacy, and Blockchain

Technical Innovations and Social Implications: Mapping Global Research Focus in AI, Blockchain, Cybersecurity, and Privacy

Contact Info

Product

Resources

About