Research Analytics Summit 2024

Document Type



VOSViewer co-authorship mapping is a powerful tool typically used for analyzing research collaboration. Users provide publication data and VOSViewer produces a map where authors are plotted on a 2-dimensional map based on how often they are in the author lists of the same publication.

In this presentation, I propose a series of tweaks to the input data that can leverage co-authorship maps to support leadership selection based on how often candidates co-author papers with their institutional peers and some of the attributes of these papers. I will suggest how best to interpret the resulting maps and address the major assumptions that must be kept in mind when using these maps for this purpose. Lastly, I will discuss the lessons learned when we offered such maps to support a series of internal leadership selections for Canada’s largest research hospital.


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