A Co-authorship network analysis of CNPq’s productivity research fellows in the probability and statistic area

Abstract

In this paper, we analyzed the co-authorship network between all CNPq’s productivity research fellows in the Probability and Statistics area in Brazil. Our aim was to describe and to understand how network measures influence researchers’ productivity. The data was gathered from the CNPq’s Lattes Platform using the software scriptLattes, and a link between two fellows represents the fact that they wrote an article together from 2009 to 2013. The network is disconnected and has only 4.7% of its possible connections. Through a regression analysis, we were able to infer that the centrality positions of an author matters to his/her productivity. As expected, closeness centrality had a negative effect on fellows’ productivity, while the degree centrality had a positive effect.

Author Cooperation Network in Biology and Chemistry Literature during 2014–2018: Construction and Structural Characteristics

“…Cimenler et al [16] collected collaborative output data of researchers in a self-reporting way, which can provide some instructions on whether collaborative research is important or not, and improved the authenticity and accuracy of the results to a certain extent. More specifically, Souza et al [17] used a co-author network to assess the mechanisms of human interaction and productivity performance in specific groups with changes in various network indicators.…”

Exploring the Co-Authorship Network Among Cnpq’s Productivity Fellows in the Area of Industrial Engineering

“…The authority also showed significant, but negative correlation. Souza et al (2016), in a co-authorship network among researchers with CNPq grant in research productivity in the area of Statistics, showed that the most productive fellows are also the most central in the network and that the metrics degree centrality and closeness centrality had a higher impact on the number of articles published by a fellow.…”