In a well-known paper [Social Networks 1 (1979) 215] Linton Freeman clarified the importance of the centrality concept in network analysis. There are a variety of centrality measures available, and they are mainly used as descriptive statistics in various network studies. For instance, actor centrality measured by vertex degree captures those aspects of centrality that have an impact on contact...

We study the h Hirsch index as a local node centrality measure for complex networks in general. The h index is compared with the Degree centrality (a local measure), the Betweenness and Eigenvector centralities (two non-local measures) in the case of a biological network (Yeast interaction protein-protein network) and a linguistic network (Moby Thesaurus II). In both networks, the Hirsch index ...

An incredible number of centrality indices has been proposed to date (Todeschini & Consonni, 2009). Four of them, however, can be considered prototypical because they operationalize distinct concepts of centrality and together cover the bulk of analyses and empirical uses: degree, closeness, betweenness, and eigenvector centrality. In teaching any mathematical science, it is instructive to cons...

With great theoretical and practical significance, locating influential nodes of complex networks is a promising issue. In this paper, we present a dynamics-sensitive (DS) centrality by integrating topological features and dynamical properties. The DS centrality can be directly applied in locating influential spreaders. According to the empirical results on four real networks for both susceptib...

Ernesto Estrada Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK The discriminant power of centrality indices for the degree, eigenvector, closeness, betweenness and subgraph centrality is analyzed. It is defined by the number of graphs for which the standard deviation of the centrality of its nodes is zero. On the basis of empirical analysis it is conclud...

Networks of social relations can be represented by graphs and socioor adjacency-matrices and their structure can be analyzed using different concepts, one of them called centrality. We will provide a new formalization of a “node-centrality” which leads to some properties a measure of centrality has to satisfy. These properties allow to test given measures, for example measures based on degree, ...

entrality egree loseness etweenness itality measures Centrality measures are based upon the structural position an actor has within the network. Induced centrality, sometimes called vitality measures, take graph invariants as an overall measure and derive vertex level measures by deleting individual nodes or edges and examining the overall change. By taking the sum of standard centrality measur...