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A. I. M. Jakaria Rahman

Publications and source records attributed to A. I. M. Jakaria Rahman.

3 recordsLinked to original sources

Measuring the match between evaluators and evaluees: Cognitive distances between panel members and research groups at the journal level

When research groups are evaluated by an expert panel, it is an open question how one can determine the match between panel and research groups. In this paper, we outline two quantitative approaches that determine the cognitive distance between evaluators and evaluees, based on the journals they have published in. We use example data from four research evaluations carried out between 2009 and 2014 at the University of Antwerp. While the barycenter approach is based on a journal map, the similarity-adapted publication vector (SAPV) approach is based on the full journal similarity matrix. Both approaches determine an entity's profile based on the journals in which it has published. Subsequently, we determine the Euclidean distance between the barycenter or SAPV profiles of two entities as an indicator of the cognitive distance between them. Using a bootstrapping approach, we determine confidence intervals for these distances. As such, the present article constitutes a refinement of a previous proposal that operates on the level of Web of Science subject categories.

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Corrigendum to "Is the expertise of evaluation panels congruent with the research interests of the research groups: a quantitative approach based on barycenters" [Journal of Informetrics 9(4) (2015) 704-721]

In Rahman, Guns, Rousseau, and Engels (2015) we described several approaches to determine the cognitive distance between two units. One of these approaches was based on what we called barycenters in N dimensions. This note corrects this terminology and introduces the more adequate term 'similarity-adapted publication vectors'.

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A note and a correction on measuring cognitive distance in multiple dimensions

In a previous article (Rahman, Guns, Rousseau, and Engels, 2015) we described several approaches to determine the cognitive distance between two units. One of these approaches was based on what we called barycenters in N dimensions. The present note corrects this terminology and introduces the more adequate term 'similarity-adapted publication vectors'. Furthermore, we correct an error in normalization and explain the importance of scale invariance in determining cognitive distance. We also consider weighted cosine similarity as an alternative approach to determine cognitive (dis)similarity. Overall, we find that the three approaches (distance between barycenters, distance between similarity-adapted publication vectors, and weighted cosine similarity) yield very similar results.

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