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Abstract

The journal structure in the China Scientific and Technical Papers and Citations Database (CSTPCD) is analyzed from three perspectives: the database level, the specialty level, and the institutional level (i.e., university journals vs. journals issued by the Chinese Academy of Sciences). The results are compared with those for (Chinese) journals included in the Science Citation Index (SCI). The frequency of journal-journal citation relations in the CSTPCD is an order of magnitude lower than in the SCI. Chinese journals, especially high-quality journals, prefer to cite international journals rather than domestic ones; however, Chinese journals do not get an equivalent reception from their international counterparts. The international visibility of Chinese journals is low, but varies among fields of science. Journals of the Chinese Academy of Sciences have a better reception in the international scientific community than university journals.

Type

a

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Abstract

Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (a) fractional counting on the impact factor (IF) and (b) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes (top-1%, top-5%, etc.). Do these approaches lead to field-normalized impact measures for journals? In addition to the 2-year IF (IF2), we consider the 5-year IF (IF5), the respective numerators of these IFs, and the number of Total Cites, counted both as integers and fractionally. These various indicators are tested against the hypothesis that the classification of journals into 11 broad fields by PatentBoard/NSF (National Science Foundation) provides statistically significant between-field effects. Using fractional counting the between-field variance is reduced by 91.7% in the case of IF5, and by 79.2% in the case of IF2. However, the differences in citation counts are not significantly affected by fractional counting. These results accord with previous studies, but the longer citation window of a fractionally counted IF5 can lead to significant improvement in the normalization across fields.

Type

a

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Abstract

Until recently, Chinese texts could not be studied using co-word analysis because the words are not separated by spaces in Chinese (and Japanese). A word can be composed of one or more characters. The online availability of programs that separate Chinese texts makes it possible to analyze them using semantic maps. Chinese characters contain not only information but also meaning. This may enhance the readability of semantic maps. In this study, we analyze 58 words which occur 10 or more times in the 1,652 journal titles of the China Scientific and Technical Papers and Citations Database. The word-occurrence matrix is visualized and factor-analyzed.

Type

a

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Type

a