Professor Mike Thelwall stands as a preeminent figure in data science and research evaluation methodologies, currently serving as Professor of Data Science at The University of Sheffield. After establishing a distinguished career spanning over three decades at the University of Wolverhampton where he taught mathematics and statistics from 1989 to 2023, he transitioned to focus on library and information science with particular emphasis on web indicators for research evaluation. In 2000, he founded the Statistical Cybermetrics and Research Evaluation Group, pioneering innovative approaches to measuring research impact through web-based metrics. His career trajectory reflects a remarkable evolution from traditional mathematical disciplines to the forefront of digital scholarship assessment. This unique perspective has positioned him as a thought leader who bridges quantitative rigor with social science applications in the evaluation of academic research.
Professor Thelwall's groundbreaking contributions to bibliometrics and scientometrics have fundamentally reshaped how research impact is measured and understood in the digital age. His development and refinement of webometric indicators provided the foundation for alternative metrics now widely adopted across academic institutions worldwide for research evaluation purposes. Currently, he leads the ESRC-funded international metascience project AI Peer, which rigorously assesses the value of large language models like ChatGPT for research evaluation processes, representing a significant evolution in his decades-long investigation of research measurement methodologies. Additionally, he participates in an international project studying scientific retractions and misinformation in the media funded by the Calouste Gulbenkian Foundation, demonstrating his commitment to addressing contemporary challenges in scholarly communication. His research consistently applies quantitative methods and artificial intelligence to social science issues with a reflexive perspective, generating influential insights that have advanced the field of research evaluation.
Beyond his technical contributions, Professor Thelwall has been instrumental in fostering interdisciplinary collaboration across diverse academic fields, from complexity science to Victorian studies, demonstrating the broad applicability of his methodological approaches. His core strengths lie in combining sophisticated programming skills with quantitative-led mixed methods research, enabling comprehensive analysis of complex social phenomena through digital traces. His ongoing research continues to push boundaries in web-based data collection, methods development and evaluation, gender analysis, and the application of emerging technologies to research assessment. Currently focused on harnessing Large Language Models for research evaluation, he remains at the cutting edge of integrating artificial intelligence with social science perspectives. Professor Thelwall's work continues to shape the future of research evaluation methodologies, ensuring they remain relevant, rigorous, and responsive to the evolving landscape of scholarly communication.
