2009/07/31 by Filippo Radicchi, Santo Fortunato, Benjamin Markines +1 · 6 citations
Computer Science · Decision Sciences · Physics and Astronomy · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #cs.DL #physics.data-an #physics.soc-ph #scientometrics and bibliometrics research
paper · pdf · doi:10.1103/physreve.80.056103
published as Phys. Rev. E 80, 056103 (2009) · Revised version. 11 pages, 10 figures, 1 table. The portal to compute the rankings of scientists is at http://www.physauthorsrank.org
arxiv created 2009/09/23 · openalex publication_date 2009/11/11 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.