Research assessment based on infrequent achievements: A comparison of the United States and Europe in terms of highly cited papers and Nobel Prizes

A leading bibliometric author does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

BACKGROUND

A total of 22,367 bibliometric articles have been indexed by Web of Science (WoS). The most significant contribution to the field has not yet been identified through bibliometric analysis. A comparison of individual research achievements (IRAs) and trend analysis of article citations are required after extracting bibliometric articles. The study aimed to confirm whether the leading author has a dominant RA and which articles are worth reading for readers using trend analysis.

METHODS

We identified authors with at least 100 articles related to bibliometrics in the WoS core collection. A total of 399 articles were collected to cluster author collaborations. Co-word analysis and chord diagrams were used to match chief authors in clusters with Keywords Plus in WoS core collection. The category, journal impact factor, authorship, and L-index (CJAL) score and the absolute advantage coefficient (AAC) were used to compare IRAs and identify the leading author who dominated the field significantly beyond the next 2 authors. In addition to network charts and chord diagrams, 4 visualizations were used to report study results, including a Sankey diagram, a dot plot, a temporal trend graph, and a radar plot. The temporal bubble graph was used to select articles that deserve to be read.

RESULTS

The top 3 authors were Lutz Bornmann, Yuh-Shan Ho, and Giovanni Abramo, with CJAL scores of 176.22, 176.02, and 112.06, respectively, from Germany, Italy, and Taiwan. Based on the weak dominance coefficient (AAC = 0.20 < 0.70), it is evident that the leading bibliometric author has no such significant power beyond the next 2 leading authors in IRAs. A trend analysis of the last 4 years was used to illustrate the 2 articles that deserve to be read.

CONCLUSION

Three leading authors were identified through a co-word analysis of bibliometrics. There was no evidence of an author who possessed a dominant position due to a lower AAC on the leading author. The CJAL score and the AAC can be applied to many bibliographical studies in the future rather than being limited to bibliometric studies that evaluate the leading authors in a field, as we did in this study.

Identifying Scientific and Technical “Unicorns”

Purpose

Using the metaphor of “unicorn,” we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing, which may provide a new pattern to understand very high impact works in science and technology.

Design/methodology/approach

When we set CT as the total citations of papers or patents in the first ten years after publication, with CT≥ 5,000 for scientific “unicorn” and CT≥ 500 for technical “unicorn,” we have an absolute standard for identifying scientific and technical “unicorn” publications.

Findings

We identify 165 scientific “unicorns” in 14,301,875 WoS papers and 224 technical “unicorns” in 13,728,950 DII patents during 2001–2012. About 50% of “unicorns” belong to biomedicine, in which selected cases are individually discussed. The rare “unicorns” increase following linear model, the fitting data show 95% confidence with the RMSE of scientific “unicorn” is 0.2127 while the RMSE of technical “unicorn” is 0.0923.

Research limitations

A “unicorn” is a pure quantitative consideration without concerning its quality, and “potential unicorns” as CT≤5,000 for papers and CT≤500 for patents are left in future studies.

Practical implications

Scientific and technical “unicorns” provide a new pattern to understand high-impact works in science and technology. The “unicorn” pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.

Originality/value

The “unicorn” pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

Identifying landmark publications in the long run using field-normalized citation data

Purpose

The purpose of this paper is to propose an approach for identifying landmark papers in the long run. These publications reach a very high level of citation impact and are able to remain on this level across many citing years. In recent years, several studies have been published which deal with the citation history of publications and try to identify landmark publications.

Design/methodology/approach

In contrast to other studies published hitherto, this study is based on a broad data set with papers published between 1980 and 1990 for identifying the landmark papers. The authors analyzed the citation histories of about five million papers across 25 years.

Findings

The results of this study reveal that 1,013 papers (less than 0.02 percent) are “outstandingly cited” in the long run. The cluster analyses of the papers show that they received the high impact level very soon after publication and remained on this level over decades. Only a slight impact decline is visible over the years.

Originality/value

For practical reasons, approaches for identifying landmark papers should be as simple as possible. The approach proposed in this study is based on standard methods in bibliometrics.

Sequence analysis of annually normalized citation counts: an empirical analysis based on the characteristic scores and scales (CSS) method

In bibliometrics, only a few publications have focused on the citation histories of publications, where the citations for each citing year are assessed. In this study, therefore, annual categories of field- and time-normalized citation scores (based on the characteristic scores and scales method: 0 = poorly cited, 1 = fairly cited, 2 = remarkably cited, and 3 = outstandingly cited) are used to study the citation histories of papers. As our dataset, we used all articles published in 2000 and their annual citation scores until 2015. We generated annual sequences of citation scores (e.g., \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left\{ {01233233221} \right\}$$\end{document}01233233221) and compared the sequences of annual citation scores of six broader fields (natural sciences, engineering and technology, medical and health sciences, agricultural sciences, social sciences, and humanities). In agreement with previous studies, our results demonstrate that sequences with poorly cited (0) and fairly cited (1) elements dominate the publication set; sequences with remarkably cited (3) and outstandingly cited (4) periods are rare. The highest percentages of constantly poorly cited papers can be found in the social sciences; the lowest percentages are in the agricultural sciences and humanities. The largest group of papers with remarkably cited (3) and/or outstandingly cited (4) periods shows an increasing impact over the citing years with the following orders of sequences: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left\{ {0123} \right\}$$\end{document}0123 (6.01%), which is followed by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left\{ {123} \right\}$$\end{document}123 (1.62%). Only 0.11% of the papers (n = 909) are constantly on the outstandingly cited level.

At what institutions did Nobel laureates do their prize-winning work? An analysis of biographical information on Nobel laureates from 1994 to 2014

In this study we examined the institutions (and countries) the Nobel laureates of the three disciplines chemistry, physics and physiology/medicine were affiliated with (from 1994 to 2014) when they did the decisive research work. To be able to frame the results at that time point, we also looked at when the Nobel laureates obtained their Ph.D./M.D. and when they were awarded the Nobel Prize. We examined all 155 Nobel laureates of the last 21 years in physics, chemistry, and physiology/medicine. Results showed that the USA dominated as a country. Statistical analysis also revealed that only three institutions can boast a larger number of Nobelists at all three time points examined: UC Berkeley, Columbia University and the Massachusetts Institute of Technology (MIT). Researcher mobility analysis made clear that most of the Nobel laureates were mobile; either after having obtained their Ph.D./M.D. or after writing significant papers that were decisive for the Nobel Prize. Therefore, we distinguished different ways of mobility between countries and between institutions. In most cases, the researchers changed institutes/universities within one and the same country (in first position: the USA, followed, by far, by the United Kingdom, Japan and Germany).