Alexander I. Pudovkin

Algorithmic procedure for finding semantically related journals

Using citations, papers and references as parameters a relatedness factor (RF) is computed for a series of journals. Sorting these journals by the RF produces a list of journals most closely related to a specified starting journal. The method appears to select a set of journals that are semantically most similar to the target journal. The algorithmic procedure is illustrated for the journal Genetics. Inter-journal citation data needed to calculate the RF were obtained from the 1996 ISI Journal Citation Reports on CD-ROM©. Out of the thousands of candidate journals in JCR©, 30 have been selected. Some of them are different from the journals in the JCR category for genetics and heredity. The new procedure is unique in that it takes varying journal sizes into account.

Why do we need algorithmic historiography

This article discusses the rationale for creating historiographs of scholarly topics using a new program called HistCiteTM, which produces a variety of analyses to aid the historian identify key events (papers), people (authors), and journals in a field. By creating a genealogic profile of the evolution, the program aids the scholar in evaluating the paradigm involved.

Rank-normalized impact factor: a way to compare journal performance across subject categories

It is well known that uninformed science administrators often use ISIs journal impact factors without taking into account the inherent citation characteristics of individual scientific disciplines. A rank normalized impact factor (rnlF) is proposed which involves use of order statistics for the complete set of journals within each JCR category. We believe the normalization procedure provides reliable and easily interpretable values. For any journal j, its rnlF is designated as rnlF1and equals (K–R1+ 1)/K, where R1 is the descending rank of journal j in its JCR category and K is the number of journals in the category. Note: JCR impact factor listings are published in descending order. The proposed rnlF is compared with normalized impact factors proposed by earlier authors. The efficacy of the rnlF is illustrated in the cases of seven highly-cited scientists, one each from seven different fields.

Algorithmic citation-linked historiography—Mapping the literature of science

There is a large literature on mapping and visualizing the scholarly literature (White & McCain, 1997; Buter & Noyons, 2001). However, none of these methods have been used to create historical displays of works on a given subject. The authors have developed a process and software called HistCite for generating chronological maps of collections resulting from searching the ISI Web of Science (WOS), SCI/SSCI/AHCI on CD-ROM or SciSearch on Dialog. Export files are created in which all cited references for source documents are captured. These files are processed by HistCite to generate tables of the most-cited works. Real time demonstrations of several topics such as bibliographic-coupling, co-citation analysis, gene flow, etc. will be provided. The HistCite software includes an expert system for detecting and editing errors or variations in cited references. Export Files of 1,000 or more records are processed in minutes on a PC. Ideally the system will be used to help the searcher quickly identify the most significant work on a topic and trace its year-by-year development.

Research evaluation. Part I: productivity and citedness of a German medical research institution

An evaluation exercise was performed involving 313 papers of research staff (66 persons) of the Deutsche Rheuma-Forschungszentrum (DRFZ) published in 2004–2008. The records and citations to them were retrieved from the Web of Science (Thomson Reuters) in March 2010. The authors compared productivity and citedness of “group leaders” vs. “regular scientists”, of “male scientists” vs. “female scientists” using citation-based indexes. It was found that “group leaders” are more prolific and cited more often than “regular scientists”, the same is true considering “male” vs. “female scientists”. The greatest contrast is observed between “female leaders” and “female regular scientists”. The above mentioned differences are significant in indexes related to the number of papers, while values of indexes characterizing the quality of papers (average citation rate per paper and similar indexes) are not substantially different among the groups compared. The mean value of percentile rank index for all the 313 papers is 58.5, which is significantly higher than the global mean value of about 50. This fact is evidence of a higher citation status, on average, of the publications from the DRFZ.

Rank normalization of impact factors will resolve Vanclay's dilemma with TRIF

The ThomsonReuters impact factor is a viable, widely used and informative measure of journal visibility and frequency of use. It is accurate, transparent and easy to use. It is a live and evolving system, that can broaden its scope and implement new features and methods. Some of Vanclay’s suggestions, like wider use of order statistics, or our suggestion of rank normalization might be implemented by JCR in the future.

Erratum to: Research evaluation. Part II: gender effects of evaluation: are men more productive and more cited than women?

Productivity and citedness of the staff of a German medical research institution are analyzed. It was found in our previous study (Pudovkin et al.: Scientometrics, doi:10.1007/s11192-012-0659-z, 2012) that male scientists are more prolific and cited more often than female scientists. We explain in our present study one of the possible causes for obtaining this result with reference to Abramo et al. (Scientometrics 84(3): 821–833, 2009), who found in the small subgroups of star scientists a higher performance of male star scientists with respect to female star scientists; but in the remaining complementary subpopulations the performance gap between the two sexes is marginal. In agreement with Abramo et al. (2009), in our small subgroup of star scientists a higher performance of male star scientists with respect to female star scientists could be found. Contrasting, in the large complementary subgroup even a slightly higher performance of female scientists with respect to male scientists was identified. The last is even stronger expressed in favor of women than Abramo’s result that the performance gap between the two sexes is truly marginal. In addition to Abramo et al. (2009), we already found in our previous study, special indexes characterizing the quality of papers (but not quantity) are not substantially different among sexes compared.

The Journal Impact Factor Should Not Be Discarded

The Journal Impact Factor (JIF) has been heavily criticized over decades. This opinion piece argues that the JIF should not be demonized. It still can be employed for research evaluation purposes by carefully considering the context and academic environment.

Journal Impact Factor Strongly Correlates with the Citedness of the Median Journal Paper

The authors test the validity of the claim that the journal IF reflects the citedness of the majority of a journals papers or, otherwise, try to disprove the widely reported myth that the IF depends on only a few highly cited papers. To show this the coefficients of correlation between the journal IF and the citation score of the median paper (by citation score) of the journals in five JCR specialty categories are calculated. The data for the analysis were collected from Thomson-Reuters Journal Citation Reports and Web of Science. About 500 journals in 5 different subject categories are considered. It was found that the coefficients of correlation, r, are very high -- close to 1. The authors believe that their finding of very high correlation of IF values and the median citation rates provides convincing evidence that IF values are not due to a few highly cited papers but rather characterizes the majority of the journals papers.

A bibliometric and historiographic analysis of the work of Tony van Raan: a tribute to a scientometrics pioneer and gatekeeper

Using the HistCite™ software and downloading searches of the Web of Science database we have created a master collection of 1,518 papers that have cited his work and several subset collections showing his impact in the field of scientometrics and research evaluation. Using the percentile rank indexes of his publications we have demonstrated his high impact in that area and have included a table of 14 of his papers in the 95th percentile of papers published in those respective journals. Using HistCite we also created several additional historiographs of his work, which clearly shows the main papers and books which have influenced his work involving bibliometrics and fractal analysis. Copyright , Beech Tree Publishing.