Feature selection and complex networks methods for an analysis of collaboration evolution in science: an application to the ISTEX digital library

International audience—In this paper, we aim to give insights about the self-organization of scientific collaboration. To that aim, we describe a new framework to monitor the evolution of a collaboration graph that models the co-authorship of research papers authors. We use community structure of the network as a high-level description of its self-organization and thus consider the evolution of the communities across time. To monitor this evolution, we describe a diachronic analysis method based on the extraction of prevalent nodes for each community. We apply this approach on data issued from the ISTEX project, a scientific digital library that contains so far more than 16 million documents and present some preliminary results and visualizations