Towards understanding longitudinal collaboration networks: a case of mammography performance research

Seyedamir Tavakoli Taba (), Liaquat Hossain (), Simon Reay Atkinson () and Sarah Lewis ()
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Seyedamir Tavakoli Taba: University of Sydney
Liaquat Hossain: University of Sydney
Simon Reay Atkinson: University of Sydney
Sarah Lewis: Brain Mind Research Institute, University of Sydney

Scientometrics, 2015, vol. 103, issue 2, No 10, 544 pages

Abstract: Abstract In this paper, we explore the longitudinal research collaboration network of ‘mammography performance’ over 30 years by creating and analysing a large collaboration network data using Scopus. The study of social networks using longitudinal data may provide new insights into how this collaborative research evolve over time as well as what type of actors influence the whole network in time. The methods and findings presented in this work aim to assist identifying key actors in other research collaboration networks. In doing so, we apply a rank aggregation technique to centrality measures in order to derive a single ranking of influential actors. We argue that there is a strong correlation between the level of degree and closeness centralities of an actor and its influence in the research collaboration network (at macro/country level).

Keywords: Research collaboration network; Mammography performance; Social network analysis; Longitudinal data; Influential actors (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11192-015-1560-3

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