A well-designed and comprehensive citation index for the social sciences and humanities has many potential uses, but has yet to be realised. Significant parts of the scholarly production in these areas are not published in international journals, but in national scholarly journals, in book chapters or in monographs. The potential for covering these literatures more comprehensively can now be investigated empirically using a complete publication output data set from the higher education sector of an entire country (Norway). We find that while the international journals in the social sciences and humanities are rather small and more dispersed in specialties, representing a large but not unlimited number of outlets, the domestic journal publishing, as well as book publishing on both the international and domestic levels, show a concentration of many publications in few publication channels. These findings are promising for a more comprehensive coverage of the social sciences and humanities.
Authors:Jesper Schneider, Birger Larsen, and Peter Ingwersen
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.