Co-author weighting in bibliometric methodology and subfields of a scientific discipline

Collaborative work and co-authorship are fundamental to the advancement of modern science. However, it is not clear how collaboration should be measured in achievement-based metrics. Co-author weighted credit introduces distortions into the bibliometric description of a discipline. It puts great weight on collaboration - not based on the results of collaboration - but purely because of the existence of collaborations. In terms of publication and citation impact, it artificially favors some subdisciplines. In order to understand how credit is given in a co-author weighted system (like the NRC's method), we introduced credit spaces. We include a study of the discipline of physics to illustrate the method. Indicators are introduced to measure the proportion of a credit space awarded to a subfield or a set of authors.Comment: 11 pages, 1 figure, 4 table

Predicting the long-term citation impact of recent publications

A fundamental problem in citation analysis is the prediction of the long-term citation impact of recent publications. We propose a model to predict a probability distribution for the future number of citations of a publication. Two predictors are used: The impact factor of the journal in which a publication has appeared and the number of citations a publication has received one year after its appearance. The proposed model is based on quantile regression. We employ the model to predict the future number of citations of a large set of publications in the field of physics. Our analysis shows that both predictors (i.e., impact factor and early citations) contribute to the accurate prediction of long-term citation impact. We also analytically study the behavior of the quantile regression coefficients for high quantiles of the distribution of citations. This is done by linking the quantile regression approach to a quantile estimation technique from extreme value theory. Our work provides insight into the influence of the impact factor and early citations on the long-term citation impact of a publication, and it takes a step toward a methodology that can be used to assess research institutions based on their most recently published work.Comment: 17 pages, 17 figure

A GPT-Based Approach for Scientometric Analysis: Exploring the Landscape of Artificial Intelligence Research

This study presents a comprehensive approach that addresses the challenges of scientometric analysis in the rapidly evolving field of Artificial Intelligence (AI). By combining search terms related to AI with the advanced language processing capabilities of generative pre-trained transformers (GPT), we developed a highly accurate method for identifying and analyzing AI-related articles in the Web of Science (WoS) database. Our multi-step approach included filtering articles based on WoS citation topics, category, keyword screening, and GPT classification. We evaluated the effectiveness of our method through precision and recall calculations, finding that our combined approach captured around 94% of AI-related articles in the entire WoS corpus with a precision of 90%. Following this, we analyzed the publication volume trends, revealing a continuous growth pattern from 2013 to 2022 and an increasing degree of interdisciplinarity. We conducted citation analysis on the top countries and institutions and identified common research themes using keyword analysis and GPT. This study demonstrates the potential of our approach to facilitate accurate scientometric analysis, by providing insights into the growth, interdisciplinary nature, and key players in the field.Comment: 29 pages, 10 figures, 5 table

Using Google scholar to estimate the impact of journal articles in education

This article discusses the potential of Google Scholar as an alternative or complement to the Web of Science and Scopus for measuring the impact of journal articles in education. Three handbooks on research in science education, language education, and educational technology were used to identify a sample of 112 accomplished scholars. Google Scholar, Web of Science, and Scopus citations for 401 journal articles published by these authors during the 5-year period from 2003 to 2007 were then analyzed. The findings illustrate the promise and pitfalls of using Google Scholar for characterizing the influence of research output, particularly in terms of differences between the three subfields in publication practices. A calibration of the growth of Google Scholar citations is also provided. © 2010 AERA.postprin

What and how long does it take to get tenure? The Case of Economics and Business Administration in Austria, Germany and Switzerland?

This paper investigates the determinants of tenure decisions in Germany, Austria and the German-speaking part of Switzerland for professorships in economics, business administration and related fields. Our data set comprises candidates who were awarded tenure as well as those who were eligible but were not tenured. We show that business candidates have a higher probability of being tenured than economists. Youth, marital status, and publications matter; gender and children do not. The market for first appointments in economics relies much more on publication performance than the market for business administration.Habilitation, tenure, academic labor market

Citations versus expert opinions: Citation analysis of Featured Reviews of the American Mathematical Society

Peer review and citation metrics are two means of gauging the value of scientific research, but the lack of publicly available peer review data makes the comparison of these methods difficult. Mathematics can serve as a useful laboratory for considering these questions because as an exact science, there is a narrow range of reasons for citations. In mathematics, virtually all published articles are post-publication reviewed by mathematicians in Mathematical Reviews (MathSciNet) and so the data set was essentially the Web of Science mathematics publications from 1993 to 2004. For a decade, especially important articles were singled out in Mathematical Reviews for featured reviews. In this study, we analyze the bibliometrics of elite articles selected by peer review and by citation count. We conclude that the two notions of significance described by being a featured review article and being highly cited are distinct. This indicates that peer review and citation counts give largely independent determinations of highly distinguished articles. We also consider whether hiring patterns of subfields and mathematicians' interest in subfields reflect subfields of featured review or highly cited articles. We reexamine data from two earlier studies in light of our methods for implications on the peer review/citation count relationship to a diversity of disciplines.Comment: 21 pages, 3 figures, 4 table

Bowling Together: Scientific Collaboration Network of Demographers at European Population Conferences.

Exploiting a unique database of metadata for papers presented at six European Population Conferences (EPC) for the years 2006-2016, this paper explores: 1) development of research in population studies; 2) trends and patterns of scientific collaboration networks among demographers; and 3) gender differences in demographic research. The data are organised in a panel format whereby each author, institution and country are linked across the six conferences. We find that collaboration among demographers has increased substantially over the past ten years. While there is no gender disparity in the likelihood of co-authoring a paper, men are significantly more likely than women to collaborate with authors from other institutions. Likewise, the fields of research vary considerably by gender where women are particularly over represented in the subfield ‘fertility and family’ whereas men dominate the subfield ‘data and methods’. Compared to other subfields, research on ‘data and methods’ is more likely to involve collaboration across multiple institutions. With respect to collaboration patterns at the institutional level, a chord diagram plot shows that scientific collaborations across institutions are more common between institutions sharing geographical proximity. Finally, using network centrality measures, we identify key demographic research institutes which play a role in driving demographic research in Europe

Concentration in Knowledge Output: A case of Economics Journals

This paper assesses the degree of author concentration in seven economics journals, which were published in India during 1990-2002. To measure the degree of author concentration, Lotka's Law was used. Moreover, we also make an exploratory analysis of the geographic, economics subfield and institutional concentration in 704 economics journals. An important finding of this paper is that specialized journals in the sample report the highest degree of author concentration. This result is quite similar to the findings by Cox and Chung (1991). Furthermore, there are several instances showing that the journals lean towards certain norms; this may affect the flow of innovative ideas into economics. We conclude that a knowledge activity, involving the high degree of concentration and a biased publication process, may affect the flow of new ideas into the discipline.Concentration, Lotka's Law