We present a method to analyse the scientific contributions between research groups. Given multiple research groups, we construct their journal proceeding graphs and then compute the similarity gap between them using network analysis. This analysis can be used for measuring similarity gap of the topics qualities between research groups' scientific contributions. We demonstrate the practicality of our method by comparing the scientific contributions by Korean researchers with those by the global researchers for information security in 2006 - 2008. The empirical analysis shows that the current security research in South Korea has been isolated from the global research trend.
The use of statistical bibliometric indicators in research evaluation emerged in the 1960s and 1970s @cite_11 , and is in wide use today due to the development of the relevant databases. These indicators provide useful output measures of activity and performance in scientific research and have become standard tools for research evaluation @cite_37 . However, some methodological problems of research evaluation at the micro level (e.g. the scientific contribution of a small research group) still remain unresolved @cite_8 @cite_16 . @cite_0 issued the problems of the bibliometric indicators for computer science in detail.
@cite_37 @cite_8 @cite_0 @cite_16 @cite_11
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An analysis of three major problems in the application of bibliometric research performance indicators is made in three separate sections. In the first section, the influence of field-dependent citation practices is analysed. The results indicate that rankings of publications from different fields, based on citation counts, can be affected seriously by differences between citation characteristics in those fields. If certain assumptions hold, one should expect high (short term) citation levels in Biochemistry, Celbiology and Biophysics. Medium citation levels are to be expected in Experimental and Molecular Physics, Physical and Organic Chemistry, Pharmacology and Plant Physiology, and low citation levels in Mathematics, Taxonomy, Pharmacognosy and Inorganic Solid State Chemistry. In the second section time-dependent factors are studied. It is shown that trend-analyses of output and impact based on bibliometric scores can be disturbed by changes in theSCI-database and in publication and citation practices. One of the disturbing factors is shown to be the inclusion of so called Books into theSCI data-base in 1977. Finally, in the third section a case is presented which illustrates the consequences of operating on incomplete bibliometric data in the evaluation of scientific performance. A completeness percentage of 99 for publication data is proposed as a standard in evaluations of the performance of small university research groups). Bibliometric measures of individual scientific achievement are of particular interest if they can be used to predict future achievement. Here we report results of an empirical study of the predictive power of the h index compared with other indicators. Our findings indicate that the h index is better than other indicators considered (total citation count, citations per paper, and total paper count) in predicting future scientific achievement. We discuss reasons for the superiority of the h index. Research evaluation is based on a representation of the research. Improving the quality of the representations cannot prevent the indicators from being provided with meaning by a receiving discourse different from the research system(s) under study. Since policy decisions affect the systems under study, this configuration generates a tension that has been driving the further development of science indicators since World War II. The article discusses historically the emergence of science indicators and some of the methodological problems involved. More recent developments have been induced by the emergence of the European Union as a supra-national level of policy coordination and by the Internet as a global medium of communication. As science, technology, and innovation policies develop increasingly at various levels and with different objectives, the evaluative discourses can be expected to differentiate with reference to the discourses in which they are enrolled. We explore if and how Microsoft Academic (MA) could be used for bibliometric analyses. First, we examine the Academic Knowledge API (AK API), an interface to access MA data, and compare it to Google Scholar (GS). Second, we perform a comparative citation analysis of researchers by normalizing data from MA and Scopus. We find that MA offers structured and rich metadata, which facilitates data retrieval, handling and processing. In addition, the AK API allows retrieving frequency distributions of citations. We consider these features to be a major advantage of MA over GS. However, we identify four main limitations regarding the available metadata. First, MA does not provide the document type of a publication. Second, the "fields of study" are dynamic, too specific and field hierarchies are incoherent. Third, some publications are assigned to incorrect years. Fourth, the metadata of some publications did not include all authors. Nevertheless, we show that an average-based indicator (i.e. the journal normalized citation score; JNCS) as well as a distribution-based indicator (i.e. percentile rank classes; PR classes) can be calculated with relative ease using MA. Hence, normalization of citation counts is feasible with MA. The citation analyses in MA and Scopus yield uniform results. The JNCS and the PR classes are similar in both databases, and, as a consequence, the evaluation of the researchers' publication impact is congruent in MA and Scopus. Given the fast development in the last year, we postulate that MA has the potential to be used for full-fledged bibliometric analyses.