Analyzing Funding Patterns and Their Evolution in Two Medical Research Topics

Abstract

This paper analyzes funding patterns and their evolution in two medical research topics: breast cancer and ovarian cancer, taking into account cross-agency and cross-national co-funding. A bibliometric analysis of 355[Formula: see text]463 papers from PubMed (273[Formula: see text]526 on breast cancer and 81[Formula: see text]937 on ovarian cancer) brought back 91 funding agencies involved in breast cancer and 65 in ovarian cancer. Additionally, the paper examined the evolution of medical subject headings (MESH) funded by agencies. An analysis of patterns in funding, co-funding, MESH, and their evolution, was carried out using social network analysis (SNA) methodology. The results show the importance of the National Cancer Institute (NCI) in both breast and ovarian cancer. The NCI achieves its policy goals by co-funding its programs with both national and cross-national agencies. Moreover, the MESH agencies co-funded in the two years studied coincided; however, it must be said that the number of agencies which participated in research funding also increased.

What semantic analysis can tell us about long term trends in the global STI policy agenda

“…For example, Huang et al ( 2016 ) compared the US and China national funding of interdisciplinary big data research through text-mining processing of funded research proposals and funding acknowledgements of publications from the Web of Science database. Other valuable results in this sphere—cross-agency and cross-national co-funding patterns—were obtained by De-Miguel-Molina et al ( 2017 ) who focused on the bibliometric analysis of scientific papers from the PubMed database and applied also Social Network Analysis methods.…”