Betweenness Centrality (BC) is an important measure used widely in complex network analysis, such as social network, web page search, etc. Computing the exact BC values is highly time consuming. Currently the fastest exact BC determining algorithm is given by Brandes, taking O(nm) time for unweighted graphs and O(nm+n log n) time for weighted graphs, where n is the number of vertices and m is t...

Group testing is a mathematical technique that uses superimposed code theory to find a specified number of distinct units among a large population, using the fewest number of tests. In this paper, we investigate the applicability of group testing in finding vertices with high betweenness centrality. Betweenness centrality (BC) is a widely applied network analysis objective, for identifying impo...

the aim of this paper is to determine if the centrality degree and density of latin-american and caribbean countries (la-c) predicts their citation based performance in academic research in the management discipline. for our analysis, we use publication data of the social science citation index in the field of ‘‘management’’ between 1988 and 2013, extracted from isi web of science. the resultin...

this research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, bonacich flow betweenness) and productivity of information science researchers. the research population includes all those researchers who have published at least one record in one of the twenty journals of information science which has an impact factor of 0.635 as a min...

Symmetries are ubiquitous in real networks and often characterize network features and functions. Here we present a generalization of network symmetry called latent symmetry, which is an extension of the standard notion of symmetry. They are defined in terms of standard symmetries in a reduced version of the network. One unique aspect of latent symmetries is that each one is associated with a s...

The safety of people and the security of the vital functions of society are among the core tasks of governments. Various networks, especially transportation networks, are important for human life. Much research has been done to analyse the vulnerability of road networks and most of the methods were based on analysing the topological structure of the network using graph theory. For instance, Dem...

Graphs (networks) are an important tool to model data in different domains, including social networks, bioinformatics and the world wide web. Most of the networks formed in these domains are directed graphs, where all the edges have a direction and they are not symmetric. Betweenness centrality is an important index widely used to analyze networks. In this paper, first given a directed network ...

We present a parallel toolkit for pairwise distance computation in massive networks. Computing the exact shortest paths between a large number of vertices is a costly operation, and serial algorithms are not practical for billion-scale graphs. We first describe an efficient parallel method to solve the single source shortest path problem on commodity hardware with no shared memory. Using it as ...

We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of the complex network theory. We show that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperat...

Important features of networks, e.g., length of shortest paths, centrality, are defined in a graph theoretical way. Bipartite graphs are frequently applied, not only in computer science (e.g. PetriNets), but in other sciences as well. They are used to represent various problems, for example, in medicine or in economy. The relations between customers and products can be represented by bipartite ...