The integrated impact indicator revisited (I3*): a non-parametric alternative to the journal impact factor

The k-index is introduced to replace the h-index to evaluate better the scientific excellence of individuals

The best possible methods are needed to evaluate the scientific excellence of individuals and research groups in order to award positions and distribute research grants with higher efficiency. It is shown here that for the symmetrical distribution of citations of an individual the currently used h-index is approximately half of the square root of the total number of citations, according to the rule of Hirsch. It is also shown that deviations from this "ideal" h-index are common and they are due to deviations in the citation distributions of different individuals. However, those deviations are not characteristic for the scientific excellence of an individual and therefore they lead only to confusion in scientific evaluation. Therefore the h-index is suggested here to be replaced by the k-index. The k-index of an individual is calculated from his/her all independent citations as self-citations cannot be considered as an indication of the excellence of any paper or its authors (the citation is independent if there is no overlap in the lists of authors of the citing and the cited paper). The k-index takes into account only partial citations for each author of multi-authored papers. In ideal case the shares of the authors in a paper are published in the same paper similarly as shares of the inventors are published in patents. If not, the share of each co-author is taken equal to the inverse of the number of authors of the given paper. The k-index of an individual is defined as the square root from the sum of his/her independent partial citations. The value of the k-index is dependent on the databank used for the citations and on the time of the measurement. If scientists of similar age working in similar fields are compared using the same databank, their personal scientific excellence will be proportional to their k-index. When the k-index is divided by the number of active scientific years, a correction can be made for different ages of different applicants. In average, the k-index has similar values, but a wider range compared to the h-index. More importantly the k-index is not biased by this or that type of citation distribution of an individual, not biased by the self-citations and not biased by the results of the co-authors. The squares of k-indexes of smaller units are additive, and so the k-index is extended to journals, publishing houses, departments, institutions, countries, continents and to the mankind.

An evaluation of percentile measures of citation impact, and a proposal for making them better

Percentiles are statistics pointing to the standing of a paper’s citation impact relative to other papers in a given citation distribution. Percentile Ranks (PRs) often play an important role in evaluating the impact of researchers, institutions, and similar lines of study. Because PRs are so important for the assessment of scholarly impact, and because citations differ greatly across time and fields, various percentile approaches have been proposed to time- and field-normalize citations. Unfortunately, current popular methods often face significant problems in time- and field-normalization, including when papers are assigned to multiple fields or have been published by more than one unit (e.g., researchers or countries). They also face problems for estimating citation counts for pre-defined PRs (e.g., the 90th PR). We offer a series of guidelines and procedures that, we argue, address these problems and others and provide a superior means to make the use of percentile methods more accurate and informative. In particular, we introduce two approaches, CP-IN and CP-EX, that should be preferred in bibliometric studies because they consider the complete citation distribution and can be accurately interpreted. Both approaches are based on cumulative frequencies in percentages (CPs). The paper further shows how bar graphs and beamplots can present PRs in a more meaningful and accurate manner.

Impact factor volatility due to a single paper: A comprehensive analysis

We study how a single paper affects the impact factor (IF) of a journal by analyzing data from 3,088,511 papers published in 11639 journals in the 2017 Journal Citation Reports of Clarivate Analytics. We find that IFs are highly volatile. For example, the top-cited paper of 381 journals caused their IF to increase by more than 0.5 points, while for 818 journals the relative increase exceeded 25%. One in 10 journals had their IF boosted by more than 50% by their top three cited papers. Because the single-paper effect on the IF is inversely proportional to journal size, small journals are rewarded much more strongly than large journals for a highly cited paper, while they are penalized more for a low-cited paper, especially if their IF is high. This skewed reward mechanism incentivizes high-IF journals to stay small to remain competitive in rankings. We discuss the implications for breakthrough papers appearing in prestigious journals. We question the reliability of IF rankings given the high IF sensitivity to a few papers that affects thousands of journals.

Web of Science as a data source for research on scientific and scholarly activity

Web of Science (WoS) is the world’s oldest, most widely used and authoritative database of research publications and citations. Based on the Science Citation Index, founded by Eugene Garfield in 1964, it has expanded its selective, balanced, and complete coverage of the world’s leading research to cover around 34,000 journals today. A wide range of use cases are supported by WoS from daily search and discovery by researchers worldwide through to the supply of analytical data sets and the provision of specialized access to raw data for bibliometric partners. A long- and well-established network of such partners enables the Institute for Scientific Information (ISI) to continue to work closely with bibliometric groups around the world to the benefit of both the community and the services that the company provides to researchers and analysts.