We consider a broad class of walk-based, parameterized node centrality measures for network analysis. These measures are expressed in terms of functions of the adjacency matrix and generalize various well-known centrality indices, including Katz and subgraph centrality. We show that the parameter can be “tuned” to interpolate between degree and eigenvector centrality, which appear as limiting c...

Liu et. al. recently proposed a minimum number of driver nodes, ND, needed to obtain full structural controllability over a directed network [1]. Driver nodes are unmatched nodes, from which there are directed paths to all matched nodes. Their most important assertion is that a system’s controllability is to a great extent encoded by the underlying network’s degree distribution, P (kin, kout). ...

Knowledge of the network structure of agonistic interactions helps to understand the formation and the development of aggressive behavior. Therefore, video observation data of 149 pigs over three different age levels were investigated for 2 days each directly after mixing (65 groups in the rearing area, 24 groups in the growing stable and 12 groups in the breeding stable). The aim of the study ...

Modularity is generally used as a measure for determining goodness of clustering. In this paper, we performed analysis on coauthorship network. The authors belong to the field of Biology related to different research and academic institutes from all over the world. We took different centrality measures such as betweenness, degree, page rank, closeness and ranked authors on the basis of these me...

The Centrality-Lethality Hypothesis states that proteins with a higher degree centrality are more likely to be lethal, i.e. proteins involved inmore interactions aremore likely to cause deathwhen knocked off. This proposition gave rise to several new investigations in which stronger associations were obtained for other centrality measures. Most of this previouswork focused on thewell known prot...

Background and Objectives: While social network analysis has left a remarkable practical impact in the healthcare field, the potential implication of this methodology in the primary health domain is poorly researched. Hence, this study aimed to explore the use and usefulness social network analysis in the context of primary health care. Methods: The health volunteers of Imam Ali Health Center...

Betweenness centrality is a distance-based invariant of graphs. In this paper, we use lexicographic product to compute betweenness centrality of some important classes of graphs. Finally, we pose some open problems related to this topic.

In online forums or virtual communities, the interactive relationships among members are similar to actual interpersonal social networks. Each member’s position in the social network affects the individual’s ability to resources for data or organized information. The position of members in networks also considerably affects the degree of opportunity to engage in activities that share individual...

A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of dis...

In recent years, Social Network Analysis (SNA) is still growing rapidly. The mapping and measurement of the interaction in SNA can be used in many areas, for example to find the most influential users to improve the marketing strategy in Small and Medium Enterprise (SME). In order to find the most influential users in a network, we can apply the centrality measurement such as degree centrality,...