Blockmodeling of co-authorship networks in library and information science in Argentina

Abstract

The paper introduces the use of blockmodeling in the micro-level exploration of the internal structure of coauthorship networks over time. Variations in scientific productivity and researcher or research group visibility were determined by observing authors' role in the core-periphery structure and crossing this information with bibliometric data. Three techniques were applied to represent the structure of collaborative science: (1) blockmodeling; (2) the Kamada-Kawai algorithm based on the similarities in co-authorships present in the documents analysed; (3) bibliometrics to determine output volume, impact and degree of collaboration from the bibliographic data drawn from publications. The results were examined to determine the extent to which the use of these two complementary approaches, in conjunction with bibliometric data, provides greater insight into the structure and characteristics of a given field of scientific endeavour. The paper describes certain features of Pajek software and how the application might be used to study research group composition, structure and dynamics. The approach involves combining bibliometric and social network analysis to explore scientific collaboration networks and monitor individual and group careers from new perspectives. The contributionof the paper is more on methodology than the conclusions drawn from the data. Its description of a small-scale case study is intended as an example for application and can be used in other disciplines. It may be very useful for the appraisal of scientific developments