Introduction. Functional magnetic resonance data acquired in a task-absent condition (``resting state'') require new data analysis techniques that do not depend on an activation model. Standard methods use either correlations with pre-specified seed regions or independent component analysis, both of which require assumptions about the source (seed-based) or validity (ICA) of a network. In this ...

The importance of the betweenness centrality measure in (on-line) social networks is well known, as well as its possible applications to various domains. However, the classical notion of betweenness centrality is not able to capture the centrality of nodes w.r.t. paths crossing different social networks. In other words, it is not able to detect those nodes of a multi-social-network scenario (ca...

Background While the temporal networks have a wide range of applications such as opportunistic communication, there are not many clustering algorithms specifically proposed for them. Methods Based on betweenness centrality for periodic graphs, we give a clustering pseudo-polynomial time algorithm for temporal networks, in which the transit value is always positive and the least common multipl...

Who is more important in a network? Who controls the flow between the nodes or whose contribution is significant for connections? Centrality metrics play an important role while answering these questions. The betweenness metric is useful for network analysis and implemented in various tools. Since it is one of the most computationally expensive kernels in graph mining, several techniques have b...

The aim of this paper is to better understand the innovation potential of a firm’s alliance network. Here we analyze the role of an alliance network in terms of the technological distance between partners, a firm’s network position (centrality) and total network density. We study how these three elements of an alliance network, apart and in combination, affect the ‘twin tasks’ in exploration, n...

We give a brief overview of the axiomatic development of betweenness relations, and investigate the connections between these and comparability graphs. Furthermore, we characterize betweenness relations induced by reflexive and antisymmetric binary relations, thus generalizing earlier results on partial orders. We conclude with a sketch of the algorithmic aspects of recognizing induced betweenn...

Betweenness centrality is a measure based on the overall amount of shortest paths passing through given vertex. A graph betweenness-uniform if all its vertices have same betweenness centrality. We study properties graphs. In particular, we show that every connected either cycle or 3-connected graph. Also, uniform graphs high maximal degree small diameter.

Background Highly dynamic social networks, where connectivity continuously changes in time, are becoming more and more pervasive. Knowledge mobilization, which refers to the use of knowledge toward the achievement of goals, is one of the many examples of dynamic social networks. Despite the wide use and extensive study of dynamic networks, their temporal component is often neglected in social n...

Betweenness centrality is a graph analytic that states the importance of a vertex based on the number of shortest paths that it is on. As such, betweenness centrality is a building block for graph analysis tools and is used by many applications, including finding bottlenecks in communication networks and community detection. Computing betweenness centrality is computationally demanding, O(V2 + ...