Automatic term identification for bibliometric mapping

Nees van Eck; Ludo Waltman; Ed Noyons; Reindert Buter

doi:10.1007/s11192-010-0173-0

Jump to Content

Scientometrics

Volume/Issue:: Volume 82: Issue 3

Automatic term identification for bibliometric mapping

Authors:

Nees van Eck

Nees van Eck

Search for other papers by Nees van Eck in
Current site
Google Scholar
PubMed

Ludo Waltman

Ludo Waltman

Search for other papers by Ludo Waltman in
Current site
Google Scholar
PubMed

Ed Noyons

Ed Noyons Leiden University Centre for Science and Technology Studies Leiden The Netherlands

Search for other papers by Ed Noyons in
Current site
Google Scholar
PubMed

, and

Reindert Buter

Reindert Buter Leiden University Centre for Science and Technology Studies Leiden The Netherlands

Search for other papers by Reindert Buter in
Current site
Google Scholar
PubMed

View More View Less

Pages:: 581–596

Online Publication Date:: 11 Feb 2010

Publication Date:: 01 Mar 2010

Article Category:: Research Article

DOI:: https://doi.org/10.1007/s11192-010-0173-0

Keywords:: Bibliometric mapping; Term map; Automatic term identification; Probabilistic latent semantic analysis; Operations research

Open access

Download PDF

Abstract

A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

Save
Cite
Email this content

Share Link

Copy this link, or click below to email it to a friend
Email this content
or copy the link directly:

https://akjournals.com/view/journals/11192/82/3/article-p581.xml
The link was not copied. Your current browser may not support copying via this button.

Link copied successfully

Collapse
Expand

Scientometrics

Print ISSN:: 0138-9130

Online ISSN:: 1588-2861

To see the editorial board, please visit the website of Springer Nature.

Manuscript submission: http://www.editorialmanager.com/scim/

For subscription options, please visit the website of Springer Nature.

Scientometrics
Language	English
Size	B5
Year of Foundation	1978
Volumes per Year	1
Issues per Year	12
Founder	Akadémiai Kiadó
Founder's Address	H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher	Akadémiai Kiadó Springer Nature Switzerland AG
Publisher's Address	H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible Publisher	Chief Executive Officer, Akadémiai Kiadó
ISSN	0138-9130 (Print)
ISSN	1588-2861 (Online)