Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research

Volume: 114, Issue: 3, Pages: 883 - 904
Published: Dec 14, 2017
Abstract
Funded research has been linked to academic production and performance. While the presence of funding acknowledgements may serve as an indicator of quality to some extent, we still lack tools to evaluate whether funding agencies allocate resources to novel and innovative research rather than mature fields. We address this issue in the present study by using bibliometrics. In particular, we exploit the citation network properties of academic...
Paper Details
Title
Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research
Published Date
Dec 14, 2017
Volume
114
Issue
3
Pages
883 - 904
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.