Search

In this paper a weighted complex network is used to detect communities of basketball players on the basis of their performances. A sparsification procedure to remove weak edges is also applied. In our proposal, at each removal of an edge the best community structure of the "giant component" is calculated, maximizing the modularity as a measure of compactness within communities and separation among communities. The "sparsification transition" is confirmed by the normalized mutual information. In this way, not only the best distribution of nodes into communities is found, but also the ideal number of communities as well. An application to community detection of basketball players for the NBA regular season 2020–2021 is presented. The proposed methodology allows a data driven decision making process in basketball. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study the dynamics of the commuting system of two insular regions of Italy, Sardinia and Sicily, inspected as complex networks. The authors refer to a 20-year time period and take into account three census data sets about the work and study-driven inter-municipal origin-destination movements of residential inhabitants in 1981, 1991 and 2001. Since it is likely that the number of municipalities (in this case, the vertices of the system) does not display sharp variations, the authors direct the study to the variation of the properties emerging through both a topological and a weighted network representation of commuting in the time periods indicated. [ABSTRACT FROM AUTHOR]