The research field called Science of Science seeks to uncover structural patterns within scientific research itself. In this project, we analyze large-scale citation networks using mathematical tools from graph and network theory, with an emphasis on openly available databases and reproducibility. Our aim is to develop bibliometric measures, such as disruption indicators, that are robust to inherent noise in the citation databases. Ideally, we hope to guide the scientific progress with evidence driven policy recommendations.
Papers
PRESENTATIONS
Large Language Models Amplify the Matthew Effect in Scientific Research
Andres Algaba, Vincent Holst, Floriano Tori, Melika Mobini, Brecht Verbeken, Sylvia Wenmackers & Vincent Ginis
Presented at the 4th International Conference on the Science of Science and Innovation in Copenhagen on June 17, 2025.
How Open Code and Data Unveiled Errors in Measuring Scientific Disruption
Vincent Holst, Andres Algaba, Floriano Tori, Sylvia Wenmackers & Vincent Ginis
Presented at the 28th International Conference on Science, Technology and Innovation Indicators in Berlin on September 20, 2024.
The Illusion of Decline: Unpacking Intrinsic Network Effects in Scientific Disruption
Vincent Holst, Andres Algaba, Floriano Tori, Sylvia Wenmackers & Vincent Ginis
Presented at the 14th Global TechMining Conference in Berlin on September 17, 2024.
Posters
The Curious Case of the Declining Disruption’s Disappearance in Science
Vincent Holst, Andres Algaba, Floriano Tori, Sylvia Wenmackers & Vincent Ginis
Presented at the 4th International Conference on the Science of Science and Innovation in Copenhagen on June 16, 2025.