Diffusion of scientific credits and the ranking of scientists Export

@article{citeulike:6100352, abstract = {Recently, the abundance of digital data is enabling the implementation of graph-based ranking algorithms that provide system level analysis for ranking publications and authors. Here, we take advantage of the entire Physical Review publication archive (1893\–2006) to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network, we define a ranking method based on a diffusion algorithm that mimics the spreading of scientific credits on the network. We compare the results obtained with our algorithm with those obtained by local measures such as the citation count and provide a statistical analysis of the assignment of major career awards in the area of physics. A website where the algorithm is made available to perform customized rank analysis can be found at the address http://www.physauthorsrank.org.}, author = {Radicchi, Filippo and Fortunato, Santo and Markines, Benjamin and Vespignani, Alessandro}, citeulike-article-id = {6100352}, citeulike-linkout-0 = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PLEEE8000080000005056103000001&idtype=cvips&gifs=yes}, citeulike-linkout-1 = {http://link.aps.org/abstract/PRE/v80/e056103}, citeulike-linkout-2 = {http://dx.doi.org/10.1103/PhysRevE.80.056103}, doi = {10.1103/PhysRevE.80.056103}, journal = {Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)}, keywords = {2009-nov-read-list, academics, algorithms, diffusion, offbeat, physics, quantifying\_quality, scientist\_ranking, scientists, statistical\_analysis}, number = {5}, pages = {056103+}, posted-at = {2009-11-14 04:40:56}, priority = {3}, publisher = {APS}, title = {Diffusion of scientific credits and the ranking of scientists}, url = {http://dx.doi.org/10.1103/PhysRevE.80.056103}, volume = {80}, year = {2009} }

TY - JOUR ID - citeulike:6100352 L3 - citeulike-article-id:6100352 N2 - Recently, the abundance of digital data is enabling the implementation of graph-based ranking algorithms that provide system level analysis for ranking publications and authors. Here, we take advantage of the entire Physical Review publication archive (1893–2006) to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network, we define a ranking method based on a diffusion algorithm that mimics the spreading of scientific credits on the network. We compare the results obtained with our algorithm with those obtained by local measures such as the citation count and provide a statistical analysis of the assignment of major career awards in the area of physics. A website where the algorithm is made available to perform customized rank analysis can be found at the address http://www.physauthorsrank.org. IS - 5 JF - Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) TI - Diffusion of scientific credits and the ranking of scientists PB - APS VL - 80 SP - 056103 KW - 2009-nov-read-list KW - academics KW - algorithms KW - diffusion KW - offbeat KW - physics KW - quantifying_quality KW - scientist_ranking KW - scientists KW - statistical_analysis AU - Radicchi, Filippo AU - Fortunato, Santo AU - Markines, Benjamin AU - Vespignani, Alessandro PY - 2009/// UR - http://dx.doi.org/10.1103/PhysRevE.80.056103 ER -