Science maps for information retrieval

Bascur Cifuentes, J.P. (2026)

Doctoral Thesis

Science maps are a widely used tool in scientometric analysis. One of their main advantages is that they reveal the structure of data, which for an analyst can both reveal unknown academic topics and address their own blind spots. These strengths make them well suited for information retrieval tasks, and researchers frequently employ science maps for this purpose. However, most existing research on science maps focuses on the accuracy of topic detection, while much less attention has been paid to their capabilities for information retrieval. This dissertation addresses this gap by exploring one overarching question: What is the effectiveness of science maps for information retrieval, and how can we enhance it?

• Science maps
• Scientometrics
• Information retrieval
• Visual analytics
• Topic clustering
• Citation networks
• Text similarity
• Academic literature search
• Bibliometric analysis
• Knowledge discovery

• All authors: Bascur Cifuentes, J.P.
• Supervisor: Waltman, L.R.; Verberne, S.
• Co-supervisor: Eck, N.J.P. van
• Committee: Barendregt, B.A.; Tijssen, R.J.W.; Kreutz, C.K.; Cabanac, G.; Velden, T.
• Qualification: Doctor (dr.)
• Awarding Institution: Centre for Science and Technology Studies (CWTS), Faculty of Social and Behavioural Sciences, Leiden University
• Date: 2026-01-21