Abstract
In developing grant proposals for funding agencies like NIH or NSF, it is often important to determine whether a research topic is gaining momentum — where by ‘momentum’ we mean the rate of change of a certain measure such as popularity, impact or significance — to evaluate whether the topic is more likely to receive grants. Analysis of data about past grant awards reveals interesting patterns about successful grant topics, suggesting it is sometimes possible to measure the degree to which a given research topic has ‘increasing momentum’. In this paper, we develop a framework for quantitative modeling of the funding momentum of a project, based on the momentum of the individual topics in the project. This momentum follows certain patterns that rise and fall in a predictable fashion. To our knowledge, this is the first attempt to quantify the momentum of research topics or projects.
This research supported by NIH grants RL1LM009833 (Hypothesis Web) and UL1DE019580, in the UCLA Consortium for Neuropsychiatric Phenomics.
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He, D., Parker, D.S. (2011). Learning the Funding Momentum of Research Projects. In: Huang, J.Z., Cao, L., Srivastava, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 6635. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20847-8_44
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DOI: https://doi.org/10.1007/978-3-642-20847-8_44
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