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Abstract  

The dynamic mapping of science using the data in theScience Citation Index was put on the research agenda of science studies byDe Solla Price in the mid 1960s. Recently, proponents of co-citation cluster analysis have claimed that in principle their methodology makes such mapping possible. The study examines this claim, both methodologically and theoretically, in relation to other means of mapping science. A detailed study of a co-citation map, its core documents' citation patterns and the related journal structures, is presented. At these three levels of possible study of aggregates of citations, an analysis is pursued for the years 1978 to 1984. The many different statistical methods which are in use for the analysis of the respective datamatrices—such as cluster analysis, factor analysis and multidimensional scalling—are assessed with a view to their potential to contribute to a better undérstanding of the dynamics at the different levels in relation to each other. This will lead to some recommendations about methods to use and to avoid when we aim at a comprehensive mapping of science. Although the study is pursued at a formal and analytical level, in the conclusions an attempt is made to reflect on the results in terms of further substantial questions for the study of the dynamics of science.

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Abstract  

In the paper we will present the adjustments we implemented on the mapping procedure. We consider them as important improvements to make the maps more user-friendly. The improvements concern the implementation of graphical user interfaces, and the addition of ‘map-external’ information. This interface enables the users of the maps to focus onto their specific areas of interest and to determine the position of actors in the field. In addition the ‘map-external’ information contributes to an objective validation of the maps. The presentation will include a demonstration of the electronic maps and added tools.

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Abstract  

Journals covered by the 2006 Science Citation Index Journal Citation Reports database have been subjected to a clustering procedure utilizing h-similarity as the underlying similarity measure. Clustering complemented with a prototyping routine provided well-conceivable results that are both compatible with and further refine existing taxonomies of science.

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Abstract  

Despite the promising introduction of bibliometric maps of science in a science policy context in the nineteen seventies, they have not been very successful yet. It seems, however, that only now they are becoming acknowledged as a useful tool. This is mainly due to the developments and integration of hypertext and graphical interfaces. Because of this, the strength of such navigation tools becomes obvious. The communication through the Internet enables the field expert (as a kind of peer review) as well as the user (from a science policy context) to contribute to the quality of the map and the interface. Moreover, the interface can provide suggestions to answer policy-related question, which is the initial purpose of such maps.

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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.

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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.

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Summary  

Mapping of science and technology can be done at different levels of aggregation, using a variety of methods. In this paper, we propose a method in which title words are used as indicators for the content of a research topic, and cited references are used as the context in which words get their meaning. Research topics are represented by sets of papers that are similar in terms of these word-reference combinations. In this way we use words without neglecting differences and changes in their meanings. The method has several advantages, such as high coverage of publications. As an illustration we apply the method to produce knowledge maps of information science.

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Abstract  

Previous attempts to map science using the co-citation clustering methodology are reviewed, and their shortcomings analyzed. Two enhancements of the methodology presented in Part I of the paper-fractional citation counting and variable level clustering—are briefly described and a third enhancement, the iterative clustering of clusters, is introduced. When combined, these three techniques improve our ability to generate comprehensive and representative mappings of science across the multidisciplinaryScience Citation Index (SCI) data base. Results of a four step analysis of the 1979SCI are presented, and the resulting map at the fourth iteration is described in detail. The map shows a tightly integrated network of approximate disciplinary regions, unique in that for the first time links between mathematics and biomedical science have brought about a closure of the previously linear arrangement of disciplines. Disciplinary balance between biomedical and physical science has improved, and the appearance of less cited subject areas, such as mathematics and applied science, makes this map the most comprehensive one yet produced by the co-citation methodology. Remaining problems and goals for future work are discussed.

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of Mathematical Sociology , 113 – 120 . Braam , R. R. Moed , H. F. Van Raan , F. J. 1991 Mapping of Science by combined

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. , Francois , C. , Polanco , X. , Using artificial neural networks for mapping of science and technology: application to patents analysis , Davis , M. , Wilson , C. S. (Eds), Proceedings of ISSI 2001 , Sydney, Australia, July 2001 , pp. 339 – 353

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