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

AutorBordons, María ; Aparicio, Javier ; González-Albo, Borja ; Díaz-Faes, Adrián A.
Palabras claveResearch Performance
Social Network Analysis
Poisson regression model
Fecha de publicación1-ene-2015
ResumenResearch networks play a crucial role in the production of new knowledge since collabo-ration contributes to determine the cognitive and social structure of scientific fields andhas a positive influence on research. This paper analyses the structure of co-authorshipnetworks in three different fields (Nanoscience, Pharmacology and Statistics) in Spain overa three-year period (2006–2008) and explores the relationship between the research per-formance of scientists and their position in co-authorship networks. A denser co-authorshipnetwork is found in the two experimental fields than in Statistics, where the network is ofa less connected and more fragmented nature. Using the g-index as a proxy for individualresearch performance, a Poisson regression model is used to explore how performance isrelated 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 rela-tionship with the g-index in the three fields. Local cohesion presents a negative relationshipwith the g-index in the two experimental fields, where open networks and the diversity ofco-authors seem to be beneficial. No clear advantages from intermediary positions (highbetweenness) or from being linked to well-connected authors (high eigenvector) can beinferred from this analysis. In terms of g-index, the benefits derived by authors from theirposition in co-authorship networks are larger in the two experimental fields than in thetheoretical one.
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