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...

Two concepts of centrality have been defined in complex networks. The first considers the centrality of a node and many different metrics for it has been defined (e.g. eigenvector centrality, PageRank, non-backtracking centrality, etc). The second is related to a large scale organization of the network, the core-periphery structure, composed by a dense core plus an outlying and loosely-connecte...

In a recent article, Zachary Neal (2011) distinguishes between centrality and power in world city networks and proposes two measures of recursive power and centrality. His effort to clarify oversimplistic interpretations of relational measures of power and position in world city networks is appreciated. However, Neal’s effort to innovate methodologically is based on theoretical reasoning that i...

Group centrality is an extension of the classical notion of centrality for individuals, to make it applicable to sets of them. We perform a SWOT (strengths, weaknesses, opportunities and threats) analysis of the use of group centrality in semantic networks, for different centrality notions: degree, closeness, betweenness, giving prominence to random walks. Among our main results stand out the r...

Network-analysis literature is rich in node-centrality measures that quantify the centrality of a node as a function of the (shortest) paths of the network that go through it. Existing work focuses on defining instances of such measures and designing algorithms for the specific combinatorial problems that arise for each instance. In this work, we propose a unifying definition of centrality that...

In real world complex networks, the importance of a node depends on two important parameters: 1. characteristics of the node, and 2. the context of the given application. The current literature contains several centrality measures that have been defined to measure the importance of a node based on the given application requirements. These centrality measures assign a centrality value to each no...

Betweenness centrality is a quantity that is frequently used to measure how ‘central’ a vertex v is. It is defined as the sum, over pairs of vertices other than v, of the proportions of shortest paths that pass through v. In this paper, we study the distribution of the betweenness centrality in random trees and related, subcritical graph families. Specifically, we prove that the betweenness cen...

Centrality is an important notion in complex networks; it could be used to characterize how influential a node or an edge is in the network. It plays an important role in several other network analysis tools including community detection. Even though there are a small number of axiomatic frameworks associated with this notion, the existing formalizations are not generic in nature. In this paper...

background: co-authorship is one of the most tangible forms of research collaboration. a co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. the present research using the social network analysis studied co-authorship network of 681 articles published in journal of research in medical...