Introducing a bibliometric index based on factor analysis

This work applies a factor analysis with VARIMAX rotation to develop a bibliometric indicator, named the Weighted Factor Index, in order to derive a new classification for journals belonging to a certain category, alternative to the one provided by the Journal Impact Factor. For this, 16 metrics from three different databases (Web of Science, Scopus and SCImago Journal Rank) are considered. The Weighed Factor Index entails the advantage of incorporating and summarizing information from all the indicators; so as to test its performance, it was applied to rank journals belonging to the category Information Science & Library Science.

A Historical Review of Classic Publications in Web of Science Category of Obstetrics and Gynecology

Classic publications in Web of Science Category of Obstetrics and Gynecology were identified by using bibliometric indicator, TCyear, total citations since publication to the end of the recent year from Web of Science Core Collection. Fourteen classic publications with TC2016 ≥ 1,000 times were analysied. We also applied a citation indicator, the Cyear, total citations in the most recent year only, to assess the recent impact of the classic publications. The results showed that the 14 classic publications were published between 1927 and 2004, and that the most productive journal were American Journal of Obstetrics and Gynecology. Citation histories were applied for impact of the classic publications after their publications. In addition, highlight of each classic articles were presented. A classic article by Sampson in 1927 was found to be the classic Sleeping Beauties in Web of Science category of obstetrics and gynecology.

Impact Factor of a Term: a Tool for Assessing Article's Future Citations and Author's Influence Based on PubMed and DBLP Collections

This article describes a new bibliometric indicator called Impact Factor of a Term (IFT) that helps to predict future impact of scientific works and/or the author. The predictive properties of IFT are proven by two examples of different collections of scientific articles. It is shown that the correlations of the current and future IFT values depending on the trend are practically similar for both collections. The graphs of IFT correlations of the current and future years depending on the number of articles with the word/term are presented. The graphs show that the higher the current frequency of the term and the number of articles with this term, the greater the correlation and stability of IFT. The stability of IFT helps to accurately predict the number of future citations. The list of the most informative words/terms with the largest total values of IFT multiplied by the current frequency is analyzed. It has been shown that the size of collection affects the stability and predictive properties of IFT. The words and terms with high IFT values allow us to judge the future impact of an article and its author based on the prediction of future citations. Such words also help identify promising research directions.

A Bibliometric Analysis of Global Scientific Research on Scrub Typhus

Objective. The rise of zoonotic diseases has become a global health issue around the world. The present study is aimed at assessing the global status and the trends in scrub typhus (ST) research. Methods. Publications related to ST studies from 1945 to 21st July 2020 were retrieved from the Scopus database. The search for the ST literature was conducted using the entry terms of the MeSH (Medical Subject Headings) database. Full research articles and reviews were included in the analysis, and no limitation to the language was specified. Key bibliometric indicator analysis was performed using Microsoft Excel, Bibliometrix (an R package), GraphPad Prism 5, and VOSviewer (version 1.6.6). Results. A total of 1567 publications were retrieved. The results revealed a significant increase in the number of ST publications over time. The documents received an average of 11.22 citations per document. Mahidol University in Thailand (258, 16.46%) was the most productive institution, while the American Journal of Tropical Medicine and Hygiene published the most ST articles (88, 5.62%). Korea (195, 12.44%) was the most productive country, followed by India (178, 11.36%) and China (106, 6.76%). Richards AL was the most productive author with 36 articles. Conclusions. The study findings provide useful insights into the global efforts and works related to the progress of ST research, which can be used to identify future research areas, such as vaccine development.

Discipline Impact Factor: Some of Its History, Some of the Author's Experience of Its Application, the Continuing Reasons for Its Use and… Next Beyond

PurposeThis work aims to consider the role and some of the 42-year history of the discipline impact factor (DIF) in evaluation of serial publications. Also, the original “symmetric” indicator called the “discipline susceptibility factor” is to be presented.Design/methodology/approachIn accordance with the purpose of the work, the methods are analytical interpretation of the scientific literature related to this problem as well as speculative explanations. The information base of the research is bibliometric publications dealing with impact, impact factor, discipline impact factor, and discipline susceptibility factor.FindingsExamples of the DIF application and modification of the indicator are given. It is shown why research and university libraries need to use the DIF to evaluate serials in conditions of scarce funding for subscription to serial publications, even if open access is available. The role of the DIF for evaluating journals by authors of scientific papers when choosing a good and right journal for submitting a paper is also briefly discussed. An original indicator “symmetrical” to the DIF (the “discipline susceptibility factor”) and its differences from the DIF in terms of content and purpose of evaluation are also briefly presented.Research limitationsThe selection of publications for the information base of the research did not include those in which the DIF was only mentioned, used partially or not for its original purpose. Restrictions on the length of the article to be submitted in this special issue of the JDIS also caused exclusion even a number of completely relevant publications. Consideration of the DIF is not placed in the context of describing other derivatives from the Garfield impact factor.Practical implicationsAn underrated bibliometric indicator, viz. the discipline impact factor is being promoted for the practical application. An original indicator “symmetrical” to DIF has been proposed in order of searching serial publications representing the external research fields that might fit for potential applications of the results of scientific activities obtained within the framework of the specific research field represented by the cited specialized journals. Both can be useful in research and university libraries in their endeavors to improve scientific information services. Also, both can be used for evaluating journals by authors of scientific papers when choosing a journal to submit a paper.Originality/valueThe article substantiates the need to evaluate scientific serial publications in library activities—even in conditions of access to huge and convenient databases (subscription packages) and open access to a large number of serial publications. It gives a mini-survey of the history of one of the methods of such evaluation, and offers an original method for evaluating scientific serial publications.

A Bibliometric Analysis and Visualization of the Scientific Publications of Universities: A Study of Hamadan University of Medical Sciences during 1992-2018

The evaluation of universities from different perspectives is important for their scientific development. Analyzing the scientific papers of a university under the bibliometric approach is one main evaluative approach. The aim of this study was to conduct a bibliometric analysis and visualization of papers published by Hamadan University of Medical Science (HUMS), Iran, during 1992-2018. This study used bibliometric and visualization techniques. Scopus database was used for data collection. 3753 papers were retrieved by applying Affiliation Search in Scopus advanced search section. Excel and VOSviewer software packages were used for data analysis and bibliometric indicator extraction. An increasing trend was seen in the numbers of HUMS's published papers and received citations. The highest rate of collaboration in national level was with Tehran University of Medical Sciences. Internationally, HUMS's researchers had the highest collaboration with the authors from the United States, the United Kingdom and Switzerland, respectively. All highly-cited papers were published in high level Q1 journals. Term clustering demonstrated four main clusters: epidemiological studies, laboratory studies, pharmacological studies, and microbiological studies. The results of this study can be beneficial to the policy-makers of this university. In addition, researchers and bibliometricians can use this study as a pattern for studying and visualizing the bibliometric indicators of other universities and research institutions.

Comparing institutional-level bibliometric research performance indicator values based on different affiliation disambiguation systems

The present study is an evaluation of three frequently used institution name disambiguation systems. The Web of Science normalized institution names and Organization Enhanced system and the Scopus Affiliation ID system are tested against a complete, independent institution disambiguation system for a sample of German public sector research organizations. The independent system is used as the gold standard in the evaluations that we perform. We study the coverage of the disambiguation systems and, in particular, the differences in a number of commonly used bibliometric indicators. The key finding is that for the sample institutions, the studied systems provide bibliometric indicator values that have only a limited accuracy. Our conclusion is that for any use with policy implications, additional data cleaning for disambiguating affiliation data is recommended.

Evaluating technological emergence using text analytics: two case technologies and three approaches

Scientometric methods have long been used to identify technological trajectories, but we have seldom seen reproducible methods that allow for the identification of a technological emergence in a set of documents. This study evaluates the use of three different reproducible approaches for identifying the emergence of technological novelties in scientific publications. The selected approaches are term counting technique, the emergence score (EScore) and Latent Dirichlet Allocation (LDA). We found that the methods provide somewhat distinct perspectives on technological. The term count based method identifies detailed emergence patterns. EScore is a complex bibliometric indicator that provides a holistic view of emergence by considering several parameters, namely term frequency, size, and origin of the research community. LDA traces emergence at the thematic level and provides insights on the linkages between emerging research topics. The results suggest that term counting produces results practical for operational purposes, while LDA offers insight at a strategic level.