The weighted impact factor: the paper evaluation index based on the citation ratio

PurposeThis study distinguishes the academic influence of different papers published in journals of the same subject or field based on the modification of the journal impact factor.Design/methodology/approachTaking SSCI journals in library and information science (LIS) as the research object, the authors first explore the skewness degree of the citation distribution of journal articles. Then, we define the paper citation ratio as the weight of impact factor to modify the journal impact factor for the evaluation of papers, namely the weighted impact factor. The authors further explore the feasibility of the weighted impact factor in evaluating papers.FindingsThe research results show that different types of skewness exist in the citation distribution of journal papers. Particularly, 94% of journal paper citations are highly skewed, while the rest are moderately skewed. The weighted impact factor has a closer correlation with the citation frequency of papers than the journal impact factor. It resolves the issue that the journal impact factor tends to exaggerate the influence of low-cited papers in journals with high impact factors or weaken the influence of high-cited papers in journals with low impact factors.Originality/valueThe weighted impact factor is constructed based on the skewness of the citation distribution of journal articles. It provides a new method to distinguish the academic influence of different papers published in journals of the same subject or field, then avoids the situation that papers published in the same journal having the same academic impact.

Global citation inequality is on the rise

Citations are important building blocks for status and success in science. We used a linked dataset of more than 4 million authors and 26 million scientific papers to quantify trends in cumulative citation inequality and concentration at the author level. Our analysis, which spans 15 y and 118 scientific disciplines, suggests that a small stratum of elite scientists accrues increasing citation shares and that citation inequality is on the rise across the natural sciences, medical sciences, and agricultural sciences. The rise in citation concentration has coincided with a general inclination toward more collaboration. While increasing collaboration and full-count publication rates go hand in hand for the top 1% most cited, ordinary scientists are engaging in more and larger collaborations over time, but publishing slightly less. Moreover, fractionalized publication rates are generally on the decline, but the top 1% most cited have seen larger increases in coauthored papers and smaller relative decreases in fractional-count publication rates than scientists in the lower percentiles of the citation distribution. Taken together, these trends have enabled the top 1% to extend its share of fractional- and full-count publications and citations. Further analysis shows that top-cited scientists increasingly reside in high-ranking universities in western Europe and Australasia, while the United States has seen a slight decline in elite concentration. Our findings align with recent evidence suggesting intensified international competition and widening author-level disparities in science.

Statistical Indicators of the Scientific Publications Importance: A Stochastic Model and Critical Look

A model of scientific citation distribution is given. We apply it to understand the role of the Hirsch index as an indicator of scientific publication importance in Mathematics and some related fields. The proposed model is based on a generalization of such well-known distributions as geometric and Sibuya laws. Real data analysis of the Hirsch index and corresponding citation numbers is given.

Partitioning highly, medium and lowly cited publications

Dividing papers based on their numbers of citations into several groups constitutes one of the most common research practices in bibliometrics and beyond. However, existing dividing methods are both arbitrary and subject to bias. This article proposes a novel approach to partition highly, medium and lowly cited publications based on their citation distribution. We utilise the whole Web of Science (WoS) dataset to demonstrate how to apply this approach to scholarly datasets and examine the robustness of our algorithm in each of the six disciplines under the WoS dataset. The codes that underlie the algorithm are available online.

Uncovering diffusion trends in computer science and physics publications

Purpose The purpose of this paper is to trace the knowledge diffusion patterns between the publications of top journals of computer science and physics to uncover the knowledge diffusion trends. Design/methodology/approach The degree of information flow between the disciplines is a measure of entropy and received citations. The entropy gives the uncertainty in the citation distribution of a journal; the more a journal is involved in spreading information or affected by other journals, its entropy increases. The citations from outside category give the degree of inter-disciplinarity index as the percentage of references made to papers of another discipline. In this study, the topic-related diffusion across computer science and physics scholarly communication network is studied to examine how the same research topic is studied and shared across disciplines. Findings For three indicators, Shannon entropy, citations outside category (COC) and research keywords, a global view of information flow at the journal level between both disciplines is obtained. It is observed that computer science mostly cites knowledge published in physics journals as compared to physics journals that cite knowledge within the field. Originality/value To the best of the authors’ knowledge, this is the first study that traces knowledge diffusion trends between computer science and physics publications at journal level using entropy, COC and research keywords.

Global Research Trends of Intuitionistic Fuzzy Set: A Bibliometric Analysis

Despite the fast growth of intuitionistic fuzzy publications, only a small part of these groundbreaking researches have significantly impacted the field. The main purpose of this paper was to identify and investigate the 100 most cited publications in the intuitionistic fuzzy field. Topic search based on the keyword “intuitionistic fuzzy” in the Science Citation Index and Social Sciences Citation Index databases was conducted to identify the 100 most cited articles. Bibliometric analysis methods were employed to describe these articles from different angles, such as the citation amount and rate, distribution among journals, institutions and countries/regions, author frequency, and citation distribution over time. This paper provides an insight on the characteristics of the highly cited intuitionistic fuzzy publications. The achievements of this study may provide useful information for researchers in the fields related to intuitionistic fuzzy.

The impact of transnational co-authorship on the scientific quality of academic researchers-Case Studies: Slovenia, Poland and Romania

The aim of this article is to contribute to the discussion about whether the scientific impact of an academic researcher (measured through bibliometrics indices as Hirsch score, citation scores or quantitative data about publications) can be accounted for by the presence of co-authors and the characteristics of the personal networks they are embedded in. With my study, I intend to demonstrate that there is statistical evidence between international co-authorship, measured through the number and the characteristics of international co-authors and the scientific impact of the researcher. Recent studies using bibliometrics and scientometrics approach shows that papers published with international co-authors may result in a higher citation rate than the ones written in a purely national manner (with national co-authors) (Glanzel & Schubert, 2001; Schmoch & Schubert, 2008). In the literature that addresses these issues, the main focus is put on international co-authorship, but my opinion is that the concept has undergone a series of methodological changes. I address these changes as a trend towards a transnational perspective. I explored the personal networks of university researchers, from three academic communities in the field of sociology. I analyzed the data using hierarchical regression models. This article is based on secondary data analysis starting from the data Hâncean used in 2016 (Hâncean & Perc, 2016). The data provided attribute and relational data for the focal nodes and their corresponding alters from Web of Science platform. Given the theoretical framework proposed by previous research (Adams, 2012; Hâncean & Perc, 2014; Glanzel & Schubert, 2004), I expected the scientific impact of an author to be positively influenced by the impact of the personal network he is embedded in. After running the analysis, the presence of transnational co-authors has a moderate impact on the citation distribution, especially for the Romania case. The biggest impact on the citation distribution, for all academic communities I included in the analysis, are the number of publications and the average number of co-authors’ citations. The description and the exploration of the data in all three communities of academic sociologists (Romania, Poland and Slovenia) will be used later in order to show new ways in which knowledge is transferred through the lens of a transnational perspective.