Tag Archives: graph embedding

CNetS faculty lead two prestigious DoD Minerva projects on the science of science

santo fortunato
yy ahn
stasa milojevic
alessandro flammini
Fil Menczer

Two CNetS teams were awarded prestigious awards from Minerva, a research initiative of the Department of Defense that supports basic social science research focusing on topics of particular relevance to U.S. national security. One of the two awards will develop Science Genome, a new quantitative framework to investigate science of science using representation learning and graph embedding. The $4.4M project will take advantage of the availability of digitized bibliographic data sets and powerful computational methods, such as machine learning with deep neural networks, to tap into hidden information present in complex scholarly graphs. The project is led by YY Ahn and also includes Staša Milojević, Alessandro Flammini, and Fil Menczer (more…). The other award aims to understand the fundamental laws ruling science dynamics: the description and prediction of the evolution of scientific fields, how to define and measure the novelty of a scientific work, how to assemble successful teams to solve a specific task, and how to define and measure the impact of scholars’ research. The $5M project is led by a consortium of seven prominent science of science experts in four US institutions, including CNetS professor Santo Fortunato (more…). Both projects have potential applications in policy-making, for institutions and funding agencies.