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"derivatives not only provide an analysis tool for social networks, and also help us simplify the layout of complex networks in a way that retains the main structural properties. Centrality derivatives also help to visually measure the centralization degree of a network and provide the necessary information for estimating other metrics, such as structural balance and uncertainty"
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This study uses bootstrap sampling procedures to determine how sampling affects the stability of 11 different network centrality measures. Results indicate that some measures are more stable than others, and that stability is also a function of network and study properties.
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