PhD Candidate Quantitative Science Studies (1.00 fte)
The objective of this project is to fundamentally improve our understanding of the ways in which science progresses and the way in which scientific knowledge accumulates. The progress of science is a key topic in sociology, history, and philosophy of science and one of considerable theoretical debate, but empirical insights are limited. Supported by computational advances and improved data access, in this project a large-scale data-driven approach will be taken in which scientific progress is studied based on the full text of scientific documents. In particular, the text surrounding the references in scientific documents will be analysed to get a detailed understanding of the way in which citing and cited documents relate to each other. This is expected to provide fundamental new insights into the way scientific knowledge accumulates.
The available data sources include bibliographic databases, Web of Science and Scopus, and a number of full-text data sources (e.g., Elsevier ScienceDirect, JSTOR, PubMed Central, and PLOS). In the project, these data sources will be integrated and computational linguistics will be used to analyse and categorize the citation links between documents. This will yield a large network of millions of citation links, where the links have been enriched by classifying the citation function and by relating them to scientific concepts. Based on this enriched citation network, three key dimensions of scientific progress will be analysed: time, discipline, and place. The time dimension considers the accumulation of scientific knowledge over time and the way new scientific ideas relate to existing ones. The discipline dimension focuses on disciplinary differences in scientific knowledge accumulation and on cross-disciplinary knowledge flows. Finally, the place dimension considers differences in scientific knowledge accumulation between countries, languages, and institutional settings.