Scientometrics

This paper presents a selection of results of a comprehensive quantitative, research literature-based study of Dutch energy research. The primary goal of this paper is to provide an overview of what bibliometric data from ISI and non-ISI databases may offer to describe the state of affairs in a scientific field. It illustrates the added value of combining bibliometric indicators of publication output, international visibility, international co-operation, and interdisciplinarity in a study of nuclear energy research in the 1980's when its budget decreased dramatically.

To comprehensively characterize the citation histories of sleeping beauties (SBs), this paper presents a derivative analysis of SB citation curves. Derivative analysis can differentiate among periods with different variation tendencies (ascending, declining or unchanged) in the number of yearly citations; these variation tendencies can be identified from successive (positive, negative or zero) derivatives. To overcome the interference caused by fluctuations in the citation curves, a smoothing method is first applied. A sleeping period appears in a citation curve as a horizontal region with a low citation count. During an awakening period, the derivatives of the curve are positive and may include a few zeros. Some SBs experience a rapid increase in yearly citations once awakened and have a short awakening period, whereas for others, the number of yearly citations increases steadily over a long awakening period. Different SBs can also show different forms based on the change in the number of yearly citations after they reach their peak, and these forms can also be distinguished through derivative analysis. Derivative analysis can be used alone to identify SBs and determine their awakening times or in combination with other methods of identifying SBs to improve their performance by assisting in the identification of abnormal SBs. Derivative analysis enables the “beauty coefficient’’ method (Ke et al. in Proc Natl Acad Sci USA 112(24):7426–7431, 2015) to determine awakening times that do not vary over time, thereby making Ke et al.’s method immune to interference due to citation fluctuations. It also allows one to determine multiple awakening times for a single SB.

Through analysis of problems of keywords and indexes used in co-word analysis, we find that the key to solving these problems is to integrate experts’ knowledge into co-word analysis. Therefore, this paper proposes a new co-word analysis: semantic-based co-word analysis which can integrate experts’ knowledge into co-word analysis effectively. The performance of this method has been proved to be very good. It can solve problems on keywords and indexes used in co-word analysis effectively and can improve the veracity of co-word analysis. Using this method, the research filed of “human intelligence network” in China has been analyzed. According to the analysis result, we point out that there are four research focuses on it in China now. They are “methods and theories of human intelligence network”, “human intelligence network”, “competitive intelligence system (CIS for short)”, “the construction and visualization of human intelligence network”. The findings of this study not only advance the state of co-word analysis research but also shed light on future research directions.

A plethora of bibliometric indicators is available nowadays to gauge research performance. The spectrum of bibliometric based measures is very broad, from purely size-dependent indicators (e.g. raw counts of scientific contributions and/or citations) up to size-independent measures (e.g. citations per paper, publications or citations per researcher), through a number of indicators that effectively combine quantitative and qualitative features (e.g. the h-index). In this paper we present a straightforward procedure to evaluate the scientific contribution of territories and institutions that combines size-dependent and scale-free measures. We have analysed in the paper the scientific production of 189 countries in the period 2006–2015. Our approach enables effective global and field-related comparative analyses of the scientific productions of countries and academic/research institutions. Furthermore, the procedure helps to identifying strengths and weaknesses of a given country or institution, by tracking variations of performance ratios across research fields. Moreover, by using a straightforward wealth-index, we show how research performance measures are highly associated with the wealth of countries and territories. Given the simplicity of the methods introduced in this paper and the fact that their results are easily understandable by non-specialists, we believe they could become a useful tool for the assessment of the research output of countries and institutions.

This paper reports on a new approach to study the linkage between science and technology. Unlike most contributions to this area we do not trace citations of scientific literature in patents but explore citations of patents in scientific literature. Our analysis is based on papers recorded in the 1996-2000 annual volumes of the CD-Edition of Science Citation Index (SCI) of the Institute for Scientific Information (ISI) and patent data provided by the US Patent and Trademark Office. Almost 30,000 US patents were cited by scientific research papers. We analysed the citation links by scientific fields and technological sectors. Chemistry-related subfields tended to cite patents more than other scientific area. Among technological sectors, chemical clearly dominates followed by drugs and medical patents as the most frequently cited categories. Further analyses included a country-ranking based on inventor-addresses of the cited patents, a more detailed inspection of the ten most cited patents, and an analysis of class-field transfers. The paper concludes with the suggestions for future research. One of them is to compare our 'reverse' citation data with 'regular' patent citation data within the same classification system to see whether citations occur, irrespectively of their directionality, in the same fields of science and technology. Another question is as to how one should interpret reverse citation linkages.

Using a random sample of 79 theorists selected from among six of Mullins' theory groups, this study attempts to empirically assess the validity of Mullins' theory group classifications. The procedure involved utilizes multiple discriminant analysis based on four demographic-academic variables standardized relative to the publication date of the first major work written by each theorist. Results of the discriminant analysis indicate 70 percent of 40 cases, for whom complete data were available, are correctly classified, based on Mullins' initial categorizations. These results show Mullins' classification schema as having considerable construct validity, as well as demonstrating the utility of using multiple discriminant analysis as a technique for assessing other classificatory systems.

Websites of China's top 100 information technology (IT) companies were examined. Link count to a company's website was found to correlate with the company's revenue, profit, and research and development expenses. This suggests that Web hyperlinks to commercial sites can be a business performance indicator and thus a source of business information. This information is useful for Web business intelligence and Web data mining. As a comparison to IT companies, China's top 100 privately owned companies were also studied. No relationship between link count and the business performance measure was found for these companies due probably to the heterogeneous nature of this group. Data collection issues for webometrics research were also explored in the study.

An incomplete bibliography (or, more generally, an incomplete Information Production Process (IPP)) can be considered as a sample from a complete one. Sampling can be done in the sources or in the items. The simplest sampling technique is the systematic one where every kth source or kth item is taken (alternatively: deleted) (kÎû). In this paper we give a definition of systematic sampling in items and sources in the framework of an IPP in which we have continuous variables. We prove the theorem that in such IPPs we have a Lotkaian size-frequency function (i.e. a decreasing power function) if and only if systematic sampling in sources is the same as systematic sampling in items. In this proof we use the well-known characterization of power functions as scale-free functions.