Scientometric analysis of geostatistics using multivariate methods |
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Authors: | Feng Zhou Huai-Cheng Guo Yuh-Shan Ho Chao-Zhong Wu |
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Affiliation: | (1) College of Environmental Sciences, Peking University, Beijing, P. R. China;(2) Intelligent Transport System Research Center, Wuhan University of Technology, Wuhan, Hubei, P. R. China;(3) College of Environmental Sciences, Peking University, Room 208, Old Geosciences Building, Beijing, 100871, China |
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Abstract: | Multivariate methods were successfully employed in a comprehensive scientometric analysis of geostatistics research, and the
publications data for this research came from the Science Citation Index and spanned the period from 1967 to 2005. Hierarchical
cluster analysis (CA) was used in publication patterns based on different types of variables. A backward discriminant analysis
(DA) with appropriate statistical tests was then conducted to confirm CA results and evaluate the variations of various patterns.
For authorship pattern, the 50 most productive authors were classified by CA into 4 groups representing different levels,
and DA produced 92.0% correct assignment with high reliability. The discriminant parameters were mean impact factor (MIF),
annual citations per publication (ACPP), and the number of publications by the first author, for country/region pattern, CA
divided the top 50 most productive countries/regions into 4 groups with 95.9% correct assignments, and the discriminant parameters
were MIF, ACCP, and independent publication (IP); for institute pattern, 3 groups were identified from the top 50 most productive
institutes with nearly 88.0% correct assignment, and the discriminant parameters were MIF, ACCP, IP, and international collaborative
publication; last, for journal pattern, the top 50 most productive journals were classified into 3 groups with nearly 98.0%
correct assignment, and its discriminant parameters were total citations, impact factor and ACCP. Moreover, we also analyzed
general patterns for publication document type, language, subject category, and publication growth. |
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