doi.org
Quantitative Methods
in Research Evaluation
Quantitative Methods in Research Evaluation: Citation Indicators, Altmetrics, and Artificial Intelligence provides a rigorous and timely examination of how quantitative indicators can be used to evaluate research quality in contemporary academia. Combining theoretical insight with extensive empirical evidence, this book offers one of the most comprehensive assessments to date of the value, limitations, and implications of citation-based metrics, altmetrics, and emerging artificial intelligence approaches in research evaluation.
Research assessment has become increasingly dependent on quantitative indicators, influencing decisions about recruitment, promotion, funding, institutional rankings, and national research policy. Yet debates continue about the extent to which metrics can meaningfully capture research quality and scholarly impact. This book addresses these questions directly through a critical and evidence-based analysis of the relationship between indicators and expert judgements of research excellence.
Drawing on the largest high-quality dataset yet assembled on the relationship between citations and research quality, Thelwall provides unprecedented insight into the performance of research indicators across different disciplines and evaluation contexts. Central to his analysis are comparisons with article-level expert assessments from the UK Research Excellence Framework (REF) 2021, enabling detailed investigation into how closely citation data and alternative metrics align with human evaluations of academic quality across the broad spectrum of scholarly fields.
In Quantitative Methods in Research Evaluation, Thelwall explores the use of indicators in the evaluation of articles, individual researchers, departments, universities, countries, and research funders. He introduces and critically analyses a wide range of commonly used metrics, discussing their methodological foundations, practical applications, and disciplinary differences. Alongside traditional citation indicators, this volume examines the growing role of altmetrics, including social media attention and online engagement measures, as well as the emerging influence of artificial intelligence and data science methods in shaping future approaches to research assessment.
One key debate within the book is its balanced assessment of the possibilities and dangers of metric-based evaluation systems. This demonstrates that while citation data and altmetrics can provide informative and valuable evidence in some contexts, they are never sufficiently precise or reliable to function as direct measures of research quality. Thelwall also explores broader concerns surrounding the use of indicators, including disciplinary bias, transparency, gaming, and the risks associated with over-reliance on quantitative assessment.
Accessible while remaining analytically complex, Quantitative Methods in Research Evaluation is an essential resource for scholars and students in bibliometrics, scientometrics, information science, and research policy. As well as this academic audience, it is also relevant to university managers, librarians, policymakers, funding organisations, and anyone involved in the design or interpretation of research evaluation systems.
By bringing together extensive empirical evidence with critical methodological reflection, this book makes a major contribution to ongoing debates about responsible research assessment and the future role of quantitative indicators in shaping higher education.
