An extensive range of metrics has been proposed to quantify the scientific impact of papers, journals, individual researchers, and institutions [1]. A recent article reviewed no less than 57 metrics used for measuring research output [2]. Nevertheless, new ways of measuring research are still being proposed. A relatively novel method for quantifying research output is Social Network Analysis (SNA) [1,3]. In this context, SNA is a method for mapping and measuring the relationships between papers, journals, researchers, and institutions. SNA allows for the capturing of aspects of scientific impact and importance not picked up by other metrics [3]. As such, metrics derived from SNA have been used as alternatives to complement more established metrics. For example, in an earlier study, Morel et al. [4] suggested nine Brazilian research institutions to be targeted by funding programmes based on SNA. The authors selected institutions interconnecting several fragments of the research network, assuming these would facilitate the exchange of knowledge throughout the network.
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