ABSTRACT
In this article, we have built a co-authorship network among researchers with CNPQ grant in research productivity (PQ) in the area of Industrial Engineering and analyze which Social Network Analysis metrics impact their productivity level. Unlike other studies that mostly analyze unweighted networks, ours explored more broadly the network since the metrics were calculated in three ways: unweighted, including the edges weights and including the edges and nodes’ attributes. Thus, the generated results are more precise and detailed since more information is obtained. We consider the h-index of the researchers as the nodes’ attributes and measured the impact using Kendall correlation. We show that geographical distance is still a barrier to collaboration among PQs in this area and that collaboration with researchers with different levels of grant has the greatest impact in the level of the grant a researcher has.
Keywords:
weighted co-authorship network; nodes’ attributes; scientific productivity
