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 ...

Social Network Analysis is employed widely as a means to compute the probability that a given message flows through a social network. This approach is mainly grounded upon the correct usage of three basic graph-theoretic measures: degree centrality, closeness centrality and betweeness centrality. We developed a model, using Semantic Social Network Analysis, that overcomes the drawbacks of gener...

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using fe...

Centrality metrics such as betweenness and closeness have been used to identify important nodes in a network. However, it takes days to months on a high-end workstation to compute the centrality of today’s networks. The main reasons are the size and the irregular structure of these networks. While today’s computing units excel at processing dense and regular data, their performance is questiona...

Acquiring the full global information is impractical, if feasible at all, in many networks with distributed operation and self-organization features. To meet scalability requirements practical protocol implementations could use local information instead, drawn from the nodes’ ego-networks, the Social Network Analysis (SNA) counterpart of centered graphs. However, in almost all these efforts the...

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (T...

Solution concepts from cooperative game theory, such as the Shapley value or the Banzhaf index, have recently been advocated as interesting extensions of standard measures of node centrality in networks. While this direction of research is promising, the computation of game-theoretic centrality can be challenging. In an attempt to address the computational issues of game-theoretic network centr...

A class of centrality measures called betweenness centralities reflects degree of participation of edges or nodes in communication between different parts of the network. The original shortest-path betweenness centrality is based on counting shortest paths which go through a node or an edge. One of shortcomings of the shortest-path betweenness centrality is that it ignores the paths that might ...