The relationship between the research performance of scientists and their position in co-authorship networks in three fields

Abstract

a b s t r a c tResearch networks play a crucial role in the production of new knowledge since collaboration contributes to determine the cognitive and social structure of scientific fields and has a positive influence on research. This paper analyses the structure of co-authorship networks in three different fields (Nanoscience, Pharmacology and Statistics) in Spain over a three-year period (2006)(2007)(2008) and explores the relationship between the research performance of scientists and their position in co-authorship networks. A denser co-authorship network is found in the two experimental fields than in Statistics, where the network is of a less connected and more fragmented nature. Using the g-index as a proxy for individual research performance, a Poisson regression model is used to explore how performance is related to different co-authorship network measures and to disclose interfield differences. The number of co-authors (degree centrality) and the strength of links show a positive relationship with the g-index in the three fields. Local cohesion presents a negative relationship with the g-index in the two experimental fields, where open networks and the diversity of co-authors seem to be beneficial. No clear advantages from intermediary positions (high betweenness) or from being linked to well-connected authors (high eigenvector) can be inferred from this analysis. In terms of g-index, the benefits derived by authors from their position in co-authorship networks are larger in the two experimental fields than in the theoretical one.

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

“…Moreover, the network had only 4.7% of its possible connections. These results from Brazil corroborate some findings about the researchers in the statistic field in other countries such as: small average distance (DE STEFANO et al, 2013) and disconnected network with low density (BORDONS et al, 2015).…”

“…Furthermore, the general idea of positive association between statisticians' performance (h-index) and their central positions in the network was confirmed. Bordons et al (2015) studied three co-authorship networks (Nanoscience, Pharmacology and Statistics) in Spain during 2006 to 2008, to analyze the trends in each field and if network measures influence the co-authors performance (g-index). The authors found that the network of the Statistic field was less dense and less connected than the others.…”

“…To analyze the academic communities and its trends, in particular those related to co-authorship, scientists frequently make use of social network analysis (SNA). The studies include areas such as Biomedical, Physics and Computer Science (NEWMAN, 2001), Biology, Physics, and Mathematics (NEWMAN, 2004), Biotechnology, Mathematics, Physics and Sociology (KRONEGGER; FERLIGOJ; DOREIAN, 2011), Nanoscience, Pharmacology and Statistics (BORDONS et al, 2015), Electrical Engineering, Information Processing, Polymer Science and Biochemistry (YOSHIKANE and KAGEURA, 2004) and Medical (YOUSEFI-NOORAIE et al, 2008) juts to cite a few. A survey on co-authorship networks could be found on Glänzel and Schubert (2004) and Kumar (2015).…”

“…SNA is also important for those interested in research performance, because there are evidences that nodes position in a co-authorship network plays an important role in author productivity (BORDONS et al, 2015). Moreover, scientists, research centers and universities are frequently evaluated by their performance.…”

“…Moreover, we also investigate how network measures influence researchers' productivity. Our interest in this particular group of scientists came from two main reasons: (i) firstly, to our knowledge, there are few and recent social network studies about the probability and statistic community, and none about Brazilians researchers in this area (BORDONS et al, 2015;DE STEFANO et al, 2013 and SAID;WEGMAN;SHARABATI, 2010); (ii) secondly, CNPq's fellows are a select group of high quality scientists and their leadership guide and promote the advance of science in Brazil. Therefore, to study how this elite group interacts could allow a better understanding on how statistical knowledge is constructed and diffused in Brazil.…”