Network analysis has emerged as a key technique in communication studies, economics, geography, history and sociology, among others. A fundamental issue is how to identify key nodes in a network, for which purpose a number of centrality measures have been developed. This paper proposes a new parametric family of centrality measures called generalized degree. It is based on the idea that a relationship to a more interconnected node contributes to centrality in a greater extent than a connection to a less central one. Generalized degree improves on degree by redistributing its sum over the network with the consideration of the global structure. Application of the measure is supported by a set of basic properties. A sufficient condition is giv...
International audienceWe show that prominent centrality measures in network analysis are all based o...
In the area of network analysis, centrality metrics play an important role in defining the “most imp...
Centrality metrics aim to identify the most relevant nodes in a network. In the literature, a broad ...
In order to understand and represent the importance of nodes within networks better, most of the stu...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
AbstractIn this paper we study how to determine the nodes that most influential to a node in the net...
A variety of node-level centrality measures, including purely structural measures (such as degree an...
Studies in Computational Intelligence, Vol 424 entitled: Complex NetworksTechnical Session 1: Networ...
The concept of centrality is often invoked in social network analysis, and diverse indices have been...
In this paper, we empirically investigate correlations among four centrality measures, originated fr...
Abstract Existing centrality measures for social network analysis suggest the im-portance of an acto...
The concept of centrality is often invoked in social network analysis, and diverse indices have been...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
We introduce delta centralities, a new class of measures of structural centrality for networks. In p...
An important problem in network analysis is understanding how much nodes are important in order to \...
International audienceWe show that prominent centrality measures in network analysis are all based o...
In the area of network analysis, centrality metrics play an important role in defining the “most imp...
Centrality metrics aim to identify the most relevant nodes in a network. In the literature, a broad ...
In order to understand and represent the importance of nodes within networks better, most of the stu...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
AbstractIn this paper we study how to determine the nodes that most influential to a node in the net...
A variety of node-level centrality measures, including purely structural measures (such as degree an...
Studies in Computational Intelligence, Vol 424 entitled: Complex NetworksTechnical Session 1: Networ...
The concept of centrality is often invoked in social network analysis, and diverse indices have been...
In this paper, we empirically investigate correlations among four centrality measures, originated fr...
Abstract Existing centrality measures for social network analysis suggest the im-portance of an acto...
The concept of centrality is often invoked in social network analysis, and diverse indices have been...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
We introduce delta centralities, a new class of measures of structural centrality for networks. In p...
An important problem in network analysis is understanding how much nodes are important in order to \...
International audienceWe show that prominent centrality measures in network analysis are all based o...
In the area of network analysis, centrality metrics play an important role in defining the “most imp...
Centrality metrics aim to identify the most relevant nodes in a network. In the literature, a broad ...