Network analysis of temporal trends in scholarly research productivity

We propose a method to identify the journals or proceedings that are most highly esteemed by a research group over some time frame. Using open publication databases, we identify the experts in the community, and analyse their publication pattern, and then use this as a guideline for evaluating scientific outputs of other groups of researchers publishing in the same domain. To illustrate the practicality of our method, we analyse the scientific output of Korean researchers in the security subject domain from 2004 to 2009, and comparing this groups’ output with that of well-known researchers. Our empirical analysis demonstrates that there is a persistent gap between these two research groups’ publications impact over this period, although the absolute number of journal publications greatly increased over recent years.

► We propose a method to analyse the scientific production for a research group, inspired by recent advances in complex network analysis.
► The proposed metrics can be used to analyse the similarity, connectedness and gaps between the research groups' publication outputs.
► As a case study, we analyse publications on information security from South Korea, and evaluate them using our proposed method.
► The experimental result shows that there is still a gap between the two research groups' publication data in 2009 at similar level to 2004.