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. Â© 2011 IEEE.
|Titolo:||On the temporal analysis of scientific network evolution|
|Data di pubblicazione:||2011|
|Appare nelle tipologie:||4.1 Articolo in Atti di convegno|