Towards a typology of research performance diversity: the case of top Hungarian players

Abstract

Measuring the intellectual diversity encoded in publication records as a proxy to the degree of interdisciplinarity has recently received considerable attention in the science mapping community. The present paper draws upon the use of the Stirling index as a diversity measure applied to a network model (customized science map) of research profiles, proposed by several authors. A modified version of the index is used and compared with the previous versions on a sample data set in order to rank top Hungarian research organizations (HROs) according to their research performance diversity. Results, unexpected in several respects, show that the modified index is a candidate for measuring the degree of polarization of a research profile. The study also points towards a possible typology of publication portfolios that instantiate different types of diversity.

Global maps of science based on the new Web-of-Science categories

“…Leydesdorff and Rafols 2009; Melkers and Hicks 2012; Porter and Youtie 2009; Soós and Kampis 2011). A detailed manual for the mapping was provided (at the website) by Ken Riopelle.…”

“…By thus adjusting to the new situation, we hope to have provided the community with a means to map inter-and multidisciplinary sets of documents in future research using the new version of the Web of Science (cf. Melkers and Hicks, 2012;Porter & Youtie, 2011;Soós & Kampis, 2011). A detailed manual for the mapping was provided (at the website) by Ken Riopelle.…”

Measuring interdisciplinarity of a research system: detecting distinction between publication categories and citation categories

“…Huang et al (2016) used the Hill-type indicator to measure interdisciplinarity for a single granted project and took the average value of the total number of projects. Sandor and George (2011) deployed their new index measuring interdisciplinarity at the institutional level in relation to Hungarian R&D organizations. Jensen and Lutkouskaya (2014) analyzed 600 laboratories' interdisciplinarity using six indicators.…”

Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence

“…Rather than relying on aggregate categories, one may try to use directly the elements as categories calculating their cognitive distance without further categorisation, as a contrast to the coarse-grained, static classification (Rafols and Meyer, 2010;Soós and Kampis, 2011). Jensen and Lutkouskaya (2014) use various measures of diversity with different categorisations in order to have a more plural view of the degree of interdisciplinarity of French national laboratories.…”