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, 2003) has been compared with the clustering structure.
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Acknowledgements
The research was supported by Steunpunt O&O Indicatoren of the Flemish Government, the National Natural Science Foundation of China (grant no. 70673019), and the China Scholarship Council. We thank Bart Thijs for his assistance in collecting and processing data.
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Zhang, L., Janssens, F., Liang, L. et al. Journal cross-citation analysis for validation and improvement of journal-based subject classification in bibliometric research. Scientometrics 82, 687–706 (2010). https://doi.org/10.1007/s11192-010-0180-1
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DOI: https://doi.org/10.1007/s11192-010-0180-1