Scientometrics
Volume/Issue:
Volume 80: Issue 1
A comparative study of first and all-author co-citation counting, and two different matrix generation approaches applied for author co-citation analyses
Authors:
Jesper Schneider Royal School of Library and Information Science Aalborg Denmark

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Birger Larsen Royal School of Library and Information Science Copenhagen Denmark

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Peter Ingwersen Royal School of Library and Information Science Copenhagen Denmark

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Pages:
103–130
Online Publication Date:
20 Mar 2009
Publication Date:
01 Jul 2009
Article Category:
Research Article
DOI:
https://doi.org/10.1007/s11192-007-2019-y
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Abstract

Aim  The present article contributes to the current methodological debate concerning author co-citation analyses. (ACA) The study compares two different units of analyses, i.e. first- versus inclusive all-author co-citation counting, as well as two different matrix generation approaches, i.e. a conventional multivariate and the so-called Drexel approach, in order to investigate their influence upon mapping results. The aim of the present study is therefore to provide more methodological awareness and empirical evidence concerning author co-citation studies. Method  The study is based on structured XML documents extracted from the IEEE collection. These data allow the construction of ad-hoc citation indexes, which enables us to carry out the hitherto largest all-author co-citation study. Four ACA are made, combining the different units of analyses with the different matrix generation approaches. The results are evaluated quantitatively by means of multidimensional scaling, factor analysis, Procrustes and Mantel statistics. Results  The results show that the inclusion of all cited authors can provide a better fit of data in two-dimensional mappings based on MDS, and that inclusive all-author co-citation counting may lead to stronger groupings in the maps. Further, the two matrix generation approaches produce maps that have some resemblances, but also many differences at the more detailed levels. The Drexel approach produces results that have noticeably lower stress values and are more concentrated into groupings. Finally, the study also demonstrates the importance of sparse matrices and their potential problems in connection with factor analysis. Conclusion  We can confirm that inclusive all-ACA produce more coherent groupings of authors, whereas the present study cannot clearly confirm previous findings that first-ACA identifies more specialties, though some vague indication is given. Most crucially, strong evidence is given to the determining effect that matrix generation approaches have on the mapping of author co-citation data and thus the interpretation of such maps. Evidence is provided for the seemingly advantages of the Drexel approach.

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Cover Scientometrics
Scientometrics
Print ISSN:
0138-9130
Online ISSN:
1588-2861

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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)

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