Identifying influential nodes in complex networks has received increasing attention for its great theoretical and practical applications in many fields. Some classical methods, such as degree centrality, betweenness centrality, closeness centrality, and coreness centrality, were reported to have some limitations in detecting influential nodes. Recently, the famous h-index was introduced to the ...

We consider variations of two well-known centrality measures, betweenness and closeness, with a different model of information spread. Rather than along shortest paths only, it is assumed that information spreads efficiently like an electrical current. We prove that the current-flow variant of closeness centrality is identical with another known measure, information centrality, and give improve...

Identifying the node spreading influence in networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the shortest distance between a target node and the node set with the highest k-core value, we present an improved method to generate the ranking list to evaluate the node spreading influenc...

Centrality is a family of metrics for characterizing the importance vertex in graph. Although large number centrality have been proposed, majority them ignores uncertainty graph data. In this paper, we formulate closeness on uncertain graphs and define batch evaluation problem that computes subset vertices an We develop three algorithms, MS-BCC , MG-BCC MGMS-BCC based sampling to approximate sp...

In two studies, college students’ achievement goals were linked to their perceptions of closeness to their parents following an exam. In Study 1, mastery-approach goals positively predicted perceived closeness immediately after an exam, prior to receiving feedback. In Study 2, mastery-approach goals again positively predicted perceived closeness, but performance–avoidance goals interacted with ...

A new characteristic (residual closeness) which can measure the network resistance is presented. It evaluates closeness after removal of vertices or links, hence two types are considered—vertices and links residual closeness. This characteristic is more sensitive than the well-known measures of vulnerability—it captures the result of actions even if they are small enough not to disconnect the g...