Robustness of network measures to link errors.
In various applications involving complex networks, network measures are employed to assess the relative importance of network nodes. However, the robustness of such measures in the presence of link inaccuracies has not been well characterized. Here we present two simple stochastic models of false and missing links and study the effect of link errors on three commonly used node centrality measures: degree centrality, betweenness centrality, and dynamical importance. We perform numerical simulations to assess robustness of these three centrality measures. We also develop an analytical theory, which we compare with our simulations, obtaining very good agreement.
Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742, USA and Metabolism Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA and Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
J
J
Platig
Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742, USA.
E
E
Ott
Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742, USA.
M
M
Girvan