On the temporal analysis of scientific network evolution

Abstract

In this paper we approach the definition of new methodologies for the visualization and the exploration of social networks and their dynamics. We 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, we chose the case of scientific communities by analyzing a portion of the arXiv repository (ten years of publications in physics). We discuss the dataset by means of both static and temporal analysis of citations and co-authorships networks. Afterward, as we consider that scientific communities are at the same time communities of practice (through co-authorship) and that a citation represents a deliberative selection of a work among others, we introduce a new transformation to capture the co-existence of citations' effects and collaboration behaviors.