Bibliometric Analysis
Bibliometric analysis uses quantitative methods to analyze scholarly publications, revealing trends, influential researchers, and knowledge structures within specific fields. Current research focuses on applying bibliometrics to emerging areas like artificial intelligence (including deep learning, large language models, and reinforcement learning), sustainable development goals, and responsible AI, often leveraging machine learning techniques for enhanced analysis and knowledge discovery. These analyses provide valuable insights for researchers, policymakers, and practitioners by illuminating research landscapes, identifying impactful contributions, and informing resource allocation and future research directions.
Papers
Artificial intelligence technologies to support research assessment: A review
Kayvan Kousha, Mike Thelwall
Predicting article quality scores with machine learning: The UK Research Excellence Framework
Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt, Petr Knoth, Matteo Cancellieri