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A topological analysis of scientific coauthorship networks

Physica A Statistical Mechanics and its ApplicationsPublished 19 September 2006Open access
Alessio Cardillo, Salvatore Scellato, Vito Latora
Citations33
SJR quartileQ2
SJR score0.67
SNIP1.08
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TL;DR

The results show that the cond-mat community has grown over the last six years, witnessed by an improvement in the connectivity properties of coauthorship graphs over the years, as confirmed by an increasing size of the largest connected component, of the global efficiency and of the clustering coefficient.

Abstract

Abstract We study coauthorship networks based on the preprints submitted to the Los Alamos cond-mat database during the period 2000–2005. In our approach two scientists are considered connected if they have coauthored one or more cond-mat preprints together in the same year. We focus on the characterization of the structural properties of the derived graphs and on the time evolution of such properties. The results show that the cond-mat community has grown over the last six years. This is witnessed by an improvement in the connectivity properties of coauthorship graphs over the years, as confirmed by an increasing size of the largest connected component, of the global efficiency and of the clustering coefficient. We have also found that the graphs are characterized by long-tailed degree and betweenness distributions, assortative degree–degree correlations, and a power-law dependence of the clustering coefficient on the node degree.

Keywords

Decision SciencesBiochemistry, Genetics and Molecular BiologyPhysics and Astronomy