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  • Author or Editor: Luka Kronegger x
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Scientometrics
Authors: Luka Kronegger, Franc Mali, Anuška Ferligoj and Patrick Doreian

Abstract

We combine two seemingly distinct perspectives regarding the modeling of network dynamics. One perspective is found in the work of physicists and mathematicians who formally introduced the small world model and the mechanism of preferential attachment. The other perspective is sociological and focuses on the process of cumulative advantage and considers the agency of individual actors in a network. We test hypotheses, based on work drawn from these perspectives, regarding the structure and dynamics of scientific collaboration networks. The data we use are for four scientific disciplines in the Slovene system of science. The results deal with the overall topology of these networks and specific processes that generate them. The two perspectives can be joined to mutual benefit. Within this combined approach, the presence of small-world structures was confirmed. However preferential attachment is far more complex than advocates of a single autonomous mechanism claim.

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Scientometrics
Authors: Zaida Chinchilla-Rodríguez, Anuska Ferligoj, Sandra Miguel, Luka Kronegger and Félix de Moya-Anegón

Abstract

The paper introduces the use of blockmodeling in the micro-level study of the internal structure of co-authorship 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) the 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 goal was 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 it can be used to study research group composition, structure and dynamics. The approach combines bibliometric and social network analysis to explore scientific collaboration networks and monitor individual and group careers from new perspectives. Its application on a small-scale case study is intended as an example and can be used in other disciplines. It may be very useful for the appraisal of scientific developments.

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