Measuring cognitive distance between publication portfolios
Journal article, 2017

We study the problem of determining the cognitive distance between the publication portfolios of two units. In this article we provide a systematic overview of five different methods (a benchmark Euclidean distance approach, distance between barycenters in two and in three dimensions, distance between similarity-adapted publication vectors, and weighted cosine similarity) to determine cognitive distances using publication records. We present a theoretical comparison as well as a small empirical case study. Results of this case study are not conclusive, but we have, mainly on logical grounds, a small preference for the method based on similarity-adapted publication vectors

Cognitive distances

Research expertise

Bootstrapping

Similarity matrices

Similarity-adapted publication vectors

Weighted cosine similarity

Barycenters

Author

Ronald Rousseau

University of Antwerp

KU Leuven

Raf Guns

University of Antwerp

Jakaria Rahman

Research support, bibliometrics and ranking

Communication and Learning in Science

Tim C. E. Engels

University of Antwerp

Journal of Informetrics

1751-1577 (ISSN)

Vol. 11 2 583-583

Subject Categories

Educational Sciences

DOI

10.1016/j.joi.2017.03.001

More information

Latest update

2/13/2019