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It is well-known that the brain is a complex network""brain areas dedicated to different functions. As such,""consisting of""it is natural to shift toward brain network from brain mapping for deeper understanding of brain functions. Although graph theoretical network metrics measuring global or local properties of network topology have been used to investigate the brain...
Based on recent advances regarding eigenspectra of adjacency matrices, derived from the random matrix theory, the paper reintroduces the global clustering coefficient as a simple means of assessing if nonrandom modules can be detected in undirected, unweighted networks.
The scope of the work is to build a framework able to study the evolution of a set of communities based on their underlying social activities. Generally, for a given community, many subgroups may exist and evolve with different and various opinions or behaviors. So, in this paper, we will focus on the identification of the potential subgroups and their potential relation/correlation corresponding...
Social media analytics is increasingly used to uncover underlying real-world phenomena. The goal of this paper is to evaluate the role of Twitter in identifying communities of influence when the "ground truth" is known. We consider the European Parliament (EP) Twitter users during a period of eight months, in which they posted over 370,000 tweets. We define influence as a retweet relation...
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