High-ranked citations percentage as an indicator of publications quality

Scientometrics - A publications quality indicator called high-ranked citations percentage (HCP) is based on an idea that good papers are well cited. HCP was computed as a portion of cumulative...     

Statistical reliability of citation frequency as an indicator of scientific impact

The article deals with the statistical problem of the difference between the mean citation frequencies of two sets of papers required to be significantly different. An analysis of citation data indicated that, as a first-order approximation, (1) The relative spread due to a short observation interval is independent of the long-term citation frequency and (2) the relative spread in long-term citation frequencies of different papers from the same author is independent of the mean citation score for the papers by that author. As a rule-of-thumb, these two sources of variance can be characterized by standard deviations of a ratio (factor) of 2 and 3, respectively. By applying these results to citation data published in the literature, it is shown that sometimes statistically unjustified conclusions have been drawn in the past.     

International alignment and scientific regard as macro-indicators for international comparisons of publications

Many international comparisons of the publication performance at themacro level are based on direct counts of citation frequencies in the ScienceCitation Index. However, these comparisons may reveal a significant negativelanguage bias for non-English-speaking countries, or other selection biases,which can be illustrated by the relation between research budgets of scientificinstitutions and SCI publications. Against this background, a two-dimensionalrepresentation, specifying for the international alignment of the nationalpublications and the journal-standardized citation impact, proves to be amore appropriate indicator base to assess the citation performance of countriessuch as Germany. In the light of a ten countries' benchmark, time seriesof these indicators for the nineties show a considerable impact of the Germanunification with a recent trend towards an adaptation of publication behaviourin East Germany towards the Western patterns. This revised version was published online in June 2006 with corrections to the Cover Date.     

The significance of the number of highly cited papers as an indicator of scientific prolificacy

After presenting arguments that the number of highly cited papers (HCPs, 25 or more citations) has some advantages as an indicator of an author's scientific impact, the paper discusses citation data of 338 university professors in departments of medicine in the Netherlands. An analysis of the distribution of HCPs over the years provides support for the following conclusions: (1) prolific researchers with a large number of HCPs usually manifest themselves already in their Ph.D. work, apparently almost independent of the scientific setting; (2) it cannot be taken for granted that a successful Ph.D. student with some HCPs connected with his/her doctoral thesis will become a prolific successful researcher; (3) it is unlikely that an unsuccessful Ph.D. student without HCPs connected with his/her doctoral thesis will turn out to be a prolific successful researcher; and (4) for researchers, just as for artists, sportsmen, etc., talent is the most decisive factor in being successful.     

Quantifying the higher-order influence of scientific publications

Scientometrics - Citation impact is commonly assessed using direct, first-order citation relations. We consider here instead the indirect influence of publications on new publications via...     

The highly cited papers of professors as an indicator of a research group's scientific performance

In the first part of the paper the citations in 1986 and 1987 of 3938 papers published in 1985 by 324 research groups in the faculties of science and of medicine of eight universities in the Netherlands are analyzed. Because of the large statistical spread of (1) the number of short-term citations of papers cited equally frequently over a long period, and (2) the number of citations over a long period of papers by the same author, short-term citation scores appear to be an unreliable indicator of a research group's contribution to science. In the second part of the paper an alternative approach is presented, based on a subdivision of the 3938 papers in papers authored by professors with 0–2, 3–8, or 9 highly cited papers (HCPs, 25 citations) to their name. Very large citation score differences were found for the three categories. For example: for papers first-authored by a professor, the average number of citations per person in 1986 and 1987 for 1985 papers was for 161 professors with 9 HCPs a factor 14 larger than for 575 professors with only 0–2 HCPs; for papers co-authored by professors, this factor was 6.6. These findings justify the conclusion that the number of HCPs scored by the professors (and other senior scientists) during their entire career is a much more reliable predictor of the performance of a research group than the number of short-term citations of the articles published by the group within a short period. A research group's contribution to science is primarily determined by the individual scientifictalents of its members.     

Evaluation of some methods for the relative assessment of scientific publications

Some bibliometric methods for the assessment of the publication activity of research units are discussed on the basis of impact factors and citations of papers. Average subfield impact factor of periodicals representing subfields in chemistry is suggested. This indicator characterizes the average citedness of a paper in a given subfield. Comparing the total sum of impact factors of corresponding periodicals divided by the number of papers published by a research team to the average subfield impact factor a publication strategy indicator can be derived. A new bibliometric indicator, relative subfield impact, is introduced which compares the number of citations received by papers of a research unit to the average subfield impact factor.     

English as lingua franca in geological scientific publications. A bibliometric analysis

The examination of three samples of geological scientific publications: (A) 9 journals from Western Europe and USA; (B) 10 up-to-date review books, and (C) 3 sections of Volume 127 (1990–1991) of theZoological Record, shows that the statement that English is now the lingua franca in geological sciences is only in part true, but reflects a desire by many people in the scientific community, a desire which may not yet have been fulfilled     

Competition for funding as an indicator of research competitiveness

Summary Research quality is the cornerstone of modern science, it is used in the understanding of reputational differences among scientific and academic institutions. Traditionally, scientific activity is measured by a set of indicators and well-established bibliometric techniques based on the number of academic papers published in top-ranked journals or on the number of citations of these papers. These indicators are usually critical in measuring differences in research performance, both at individual and at scientific institutional levels. In this paper, we introduce an alternative and complementary set of indicators based on the results of competition for research funding, that aims to enlarge the framework in which research performance has traditionally been measured. Theoretical support for this paper is found in the role that the search for funding plays in the researchers’ credibility cycle as well as in peer review, the basic instrument for the allocation of public R&D funds. Our method analyses the outcomes of the researchers’ struggle for funding, using data from research proposal applications and awards, as the unit of observation, and aggregating them by research institutions to rank them in relative scales of research competitiveness.     

Ranking scientific publications considering the aging characteristics of citations

Ranking the significance of scientific publications has been a challenging topic for a long time. So far, many ranking methods have been proposed, one of which is the well-known PageRank algorithm. In this paper, we introduce aging characteristics to the PageRank algorithm via considering only the first 10 year citations when aggregating resource from different nodes. The validation of our new method is performed on the data of American Physical Society journals. The results indicate that taking into account aging characteristics improves the performance of the PageRank algorithm in terms of ranking accuracy for both papers and authors. Though our method is only applied to citation networks in this paper, it can be naturally used in many other real systems and similar improvements are expected.

     

Delineating the scientific footprint in technology: Identifying scientific publications within non-patent references

Indicators based on non-patent references (NPRs) are increasingly being used for measuring and assessing science–technology interactions. But NPRs in patent documents contain noise, as not all of them can be considered ‘scientific’. In this article, we introduce the results of a machine-learning algorithm that allows identifying scientific references in an automated manner. Using the obtained results, we analyze indicators based on NPRs, with a focus on the difference between NPR- and scientific non-patent references-based indicators. Differences between both indicators are significant and dependent on the considered patent system, the applicant country and the technological domain. These results signal the relevancy of delineating scientific references when using NPRs to assess the occurrence and impact of science–technology interactions.     

An approach to improve the indicator weights of scientific and technological competitiveness evaluation of Chinese universities

As indicator weights obtaining is often difficult in all types of evaluation, this paper describes an approach to improve the indicator weights of scientific and technological competitiveness evaluation of Chinese universities. As a public institution funded by Chinese government, the research center for Chinese science evaluation of Wuhan University has completed five annual evaluations for the scientific and technological competitiveness of Chinese universities since 2005, whose abundant and reliable data motivated us to try to improve the weights obtained by the AHP (analytical hierarchy process). Based on these data, we calculated the objective weights of the indicator using the representative mathematical methods of the least square and the variation coefficient. As the weights of AHP can be influenced by the knowledge, experience and preference of experts and the calculated objective weights neglect the subjective judgement information, we integrated the subjective and objective weights by respectively using the additive and multiplicative model to reflect both the subjective considerations of experts and the objective information, and obtained three kinds of integrative weights. Finally, we selected the integrative weights of multiplicative model as the best weights by comparing and analyzing the evaluation results in 2005 and 2009 of each kind of weights. The results show that the evaluation effect of the weights of multiplicative model is indeed the best for all types of Chinese universities among these kinds of weights, and the experts and university principals enquired also basically reached a consensus on the university rankings of the integrative weights of multiplicative model.     

A refinement strategy for identification of scientific software from bioinformatics publications

In the field of bioinformatics, a large number of classical software becomes a necessary research tool. To measure the influence of scientific software as one kind of important intellectual products, a few strategies have been proposed to identify the software names from full texts of papers to collect the usage data of packages in bioinformatics research. However, the performance of these strategies is limited because of the highly imbalance of data in the full texts. This study proposes EnsembleSVMs-CRF, a two-step refinement strategy based on ensemble learning that gradually increases the sentences that contain software mentions to improve the performance of named entity recognition. The experiment on the bioinformatics corpus shows that the performance of EnsembleSVMs-CRF, in terms of the local F1 (78.81%) and the global F1-A (73.49%), is superior to the rule-based bootstrapping method and direct CRF. Application of this strategy to the articles published between 2013 and 2017 in 27 bioinformatics journals extracted 8,239 unique packages. The most popular 50 packages thus identified demonstrate that most of them are professional software which generally requires inter-discipline knowledge, rather than programming skill. Meanwhile, we found that researchers in bioinformatics tend to use free scientific software, and the application of general software is increasing compared with professional software.

     

Distribution of scientific experts as recognized by peer consensus

Peer review plays an important role in maintaining the quality of science. Selection of peers is at the heart of the process by which science advances. Editors and others responsible for selecting a group of peers often rely on their position in a network by which experts in a field are linked to one another by bonds of common interest and recognized expertise. In this paper, we report one aspect of a study aimed at characterizing the structure of this network: the asymmetry of the fraction of experts receiving varying numbers of nominations as experts by peers. The distribution of such nominations is very skew, and we have found that a law of cumulative advantage provides the best theoretical approximation for the distribution of nominations, expecially when the overall pool of data is broken down into well-defined specialties.     

The standard impact factor as an evaluation tool of science fields and scientific journals

The standard impact factor for particular fields of science (Ig) and the relative impact factor K for scientific journals are introduced. The technique of calculation of standard impact factor (Ig) for a field is an inherent part of a method which allows a cross-field evaluation of scientific journals. This method for evaluating scientific journals elaborated in 1988 was aimed at the analysis of Russian journals covered by the SCI database, it was also used for chemical journals (more that 300) and for journals in the Life sciences (more than 1000). The results are discussed.     

科研、生产融合与工效学评价

文章论述企业要摆脱困境，在竞争中立于不败之地，必须不断推出新产品，满足消费者日益发展的需要。新产品的来源，一是靠自己开发，二是靠外部引进，三是引用科研部门的研究成果，将其转化为产品。研究成果的转化，如何更好地体现工效？作者建议强化科研与生产融合、开展成果与产品的工效学评价，使科研、生产、商业流通形成一体化，实现良性循环     

An approach for detecting the commonality and specialty between scientific publications and patents

Scientometrics - Scientific publications and patents are usually viewed as respective proxies of scientific research and technical development. There is considerable effort spent towards...     

Tweet Coupling: a social media methodology for clustering scientific publications

Scientometrics - We argue that classic citation-based scientific document clustering approaches, like co-citation or Bibliographic Coupling, lack to leverage the social-usage of the scientific...     

Hall transducer as an UHF power indicator

Conclusions Hall transducers made of n-type germanium can be used as sufficiently efficient power indicators in the long-wave portion of the UHF range for medium power. A wattmeter of that type using a Hall transducer described above in conjunction with high quality resonators has a linear scale and a sensitivity of 1 V per 4 m W. The error in measuring power evaluated by deviations from the mean does not exceed ±5%.     

Delimitation of scientific subfields using cognitive words from corporate addresses in scientific publications

An appropriate delimitation of scientific subfields constitutes one of the key problems in bibliometrics. Several methods have been explored for this task. The main ones are co-citation analysis, co-word analysis, the use of indexing systems based on controlled or uncontrolled keywords, and finally the use of a classification of scientific journals into subfields or categories. In our contribution we will explore a new method, which is based on cognitive words from addresses (corporate sources) in scientific publications. Cognitive address words are words referring to scientific (sub)fields, methods or objects of research, that appear in the institutional affiliations of the publishing authors (e.g., Department of Pharmacology, AIDS Research Center). We will focus on theScience Citation Index (SCI), published by the Institute for Scientific Information. Our methods will be applied to a multidisciplinary set of articles extracted from the journalsScience andNature.