Search Results
Abstract
The objective of this study is to use a clustering algorithm based on journal cross-citation to validate and to improve the journal-based subject classification schemes. The cognitive structure based on the clustering is visualized by the journal cross-citation network and three kinds of representative journals in each cluster among the communication network have been detected and analyzed. As an existing reference system the 15-field subject classification by Glänzel and Schubert (Scientometrics 56:55–73, <cite>2003</cite>) has been compared with the clustering structure.
. Glänzel , W , Schubert , A , Czerwon , HJ 1999 An item-by-item subject classification of papers published in multidisciplinary and general journals using reference analysis . Scientometrics 44 3 427 – 439 10.1007/BF02458488
Abstract
The delimitation of a research field in bibliometric studies presents the problem of the diversity of subject classifications used in the sources of input and output data. Classification of documents according to thematic codes or keywords is the most accurate method, mainly used in specialised bibliographic or patent databases. Classification of journals in disciplines presents lower specificity, and some shortcomings as the change over time of both journals and disciplines and the increasing interdisciplinarity of research. Differences in the criteria in which input and output data classifications are based obliges to aggregate data in order to match them. Standardization of subject classifications emerges as an important point in bibliometric studies in order to allow international comparisons, although flexibility is needed to meet the needs of local studies.
Abstract
A serious shortcoming of bibliometric studies based on the(Social) Science (s) Citation Index is the lack of an universally applicable subject classification scheme as individual papers are concerned. Subject classification of papers on the basis of assigning journals to subject categories (like those found in the various supplements of ISI databases) works well in case of highly specialised journals, but fails for multidisciplinary journals such asNature, Science andPNAS—and so far as subfields are taken into consideration-also for “general” journals (e.g.JACS orAngewandte Chemie). This study presents the results of a pilot project attempting to overcome this shortcoming by delimiting the subject of papers published in multidisciplinary and general journals by an item-by-item subject classification scheme, where assignment is based on the analysis of the subject classification of reference literature. The results clearly confirmed the conclusions of earlier studies by the authors in the field of reference analysis. For the really important journals (sufficiently high number of annual publications and high impact with respect to the field), the share of classifiable papers was surprisingly high, and the assignment proved reliable as well. Since papers in the leading general and multidisciplinary journals are frequently citing general and multidisciplinary journals, an iterated application of the procedure is expected to increase the number of classifiable publications. The results of the new methodology may improve the validity of bibliometric studies for research evaluation purposes.
Abstract
A serious shortcoming of bibliometric studies based on theSocial Sciences Citation Index is the lack of a universally applicable subject classification scheme as individual papers are concerned. Moreover, the selective coverage of more than thousand scientific journals per annum proved to be an insuperable obstacle in the delimitation of social science subject areas. Subject classification of papers on the basis of assigning journals to subject categories (like those found in the various supplements of ISI databases) works well in case of fully covered and highly specialised journals in the social sciences, too, but fails for multidisciplinary and selectively covered journals. This study presents the results of an item-by-item subject classification approach, where assignment is based on the analysis of the subject categories of reference literature. This analysis extends the results of an earlier study by the authors on the possibility of delimiting subfields in the hard and life sciences based on reference analysis. The assignment proved also reliable for a considerable share of literature in the social sciences. Due to the peculiarities of the database this share is lower in the SSCI than that in the SCI. Although an iterated application of the procedure is expected to increase the number of classifiable publications, it is suggested that in the sociated sciences the method should be used in combination with other means of subject assignment.
. Mendez , A. 1996 Coping with the problem of subject classification Scientometrics 35 2 223 – 235 . 14
research policies . Brussels, 2001 . 9. Noma , E. Gee , H. H. Harris , M. 1986 Subject classification and
Summary In the present study full-text analysis and traditional bibliometric methods are combined to improve the efficiency of the individual methods in the mapping of science. The methodology is applied to map research papers from a special issue of Scientometrics. The outcomes substantiate that such hybrid methodology can be applied to both research evaluation and information retrieval. The subject classification given by the guest-editors of the special issue is used for validation purposes. Because of the limited number of papers underlying the study the paper is considered a pilot study that will be extended in a later study on the basis of a larger corpus.
tracking mathematicians’ institutional affiliations. MathSciNet’ s Mathematics subject classification (MSC) system serves as an authoritative way to classify mathematical work by topic and by subdiscipline. As described in the following
for constructing a subject classification framework under the background of analyses of topics studied in LIS to investigate and analyze future research development and the paradigm shift in LIS using the proposed subject classification framework and
