A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS

By Nees Jan van Eck, Ludo Waltman, Rommert Dekker, Jan van den Berg. J. Assoc. Inf. Sci. Technol., 2010

834 citations recorded by the source corpus.

VOS is a new mapping technique that can serve as an alternative to the well-known technique of multidimensional scaling. We present an extensive comparison between the use of multidimensional scaling and the use of VOS for constructing bibliometric maps. In our theoretical analysis, we show the mathematical relation between the two techniques. In our experimental analysis, we use the techniques for constructing maps of authors, journals, and keywords. Two commonly used approaches to bibliometric mapping, both based on multidimensional scaling, turn out to produce maps that suffer from artifacts. Maps constructed using VOS turn out not to have this problem. We conclude that in general maps constructed using VOS provide a more satisfactory representation of a data set than maps constructed using well-known multidimensional scaling approaches.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/af500c33bfbae242c507ce3c96ac43e7b4f56b40

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. Nees Jan van Eck
  2. Ludo Waltman
  3. Ed C. M. Noyons
  4. Enrique Herrera-Viedma
  5. Manuel Jesus Cobo
  6. Sara Hammer
  7. M. Healy
  8. Peter Mcilveen

In Computer Vision and Pattern Recognition

  1. Ludo Waltman
  2. Nees Jan van Eck
  3. Ed C. M. Noyons
  4. Hai L. Vu
  5. Xin Zou
  6. W. Yue
  7. Chaomei Chen
  8. Enrique Herrera-Viedma

In Statistical and Nonlinear Physics

  1. Ludo Waltman
  2. Nees Jan van Eck
  3. Hai L. Vu
  4. Xin Zou
  5. W. Yue
  6. Andrew Kirby
  7. Ed C. M. Noyons
  8. Chaomei Chen

Citations in the corpus