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In this paper, the authors approach the definition of new methodologies for the visualization and the exploration of social networks and their dynamics. They present a recently introduced formalism called TVG (for Time-Varying Graphs), which was initially developed to model and analyze highly-dynamic and infrastructure-less communication networks, and TVG derived metrics. As an application context, they chose the case of scientific communities by analyzing a portion of the arXiv repository (ten years of publications in physics). They discuss the dataset by means of both static and temporal analysis of citations and co-authorships networks.
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