Klavans R, Boyack KW "Identifying a better measure of relatedness for mapping science " JASIST 57 (2): 251-263 JAN 15 2006

[Eugene Garfield]

E-mail Addresses:
Richard Klavans : rklavans at mapofscience.com
Kevin W. Boyack : kboyack at sandia.gov


Title: Identifying a better measure of relatedness for mapping science

Author(s): Klavans R, Boyack KW

Source: JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND
TECHNOLOGY 57 (2): 251-263 JAN 15 2006

Document Type: Article  Language: English
Cited References: 41   Times Cited: 0

Abstract:
Measuring the relatedness between bibliometric units (journals, documents,
authors, or words) is a central task in bibliometric analysis. Relatedness
measures are used for many different tasks, among them the generating of
maps, or visual pictures, showing the relationship between all items from
these data. Despite the importance of these tasks, there has been little
written on how to quantitatively evaluate the accuracy of relatedness
measures or the resulting maps. The authors propose a new framework for
assessing the performance of relatedness measures and visualization
algorithms that contains four factors: accuracy, coverage, scalability, and
robustness. This method was applied to 10 measures of journal-journal
relatedness to determine the best measure. The 10 relatedness measures were
then used as inputs to a visualization algorithm to create an additional 10
measures of journal-journal relatedness based on the distances between
pairs of journals in two-dimensional space. This second step determines
robustness (i.e., which measure remains best after dimension reduction).
Results show that, for low coverage (under 50%) the Pearson correlation is
the most accurate raw relatedness measure. However, the best overall
measure, both at high coverage, and after dimension reduction, is the
cosine index or a modified cosine index. Results also showed that the
visualization algorithm increased local accuracy for most measures.
Possible reasons for this counterintuitive finding are discussed.


Addresses: Klavans R (reprint author), SciTech Strategies Inc, 2405 White
Horse Rd, Berwyn, PA 19312 USA
SciTech Strategies Inc, Berwyn, PA 19312 USA
Sandia Natl Labs, Albuquerque, NM 87185 USA

E-mail Addresses: rklavans at mapofscience.com, kboyack at sandia.gov

Publisher: JOHN WILEY & SONS INC, 111 RIVER ST, HOBOKEN, NJ 07030 USA
Subject Category: COMPUTER SCIENCE, INFORMATION SYSTEMS; INFORMATION
SCIENCE & LIBRARY SCIENCE
IDS Number: 000VM

ISSN: 1532-2882

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