Proceedings

EPJ B Highlight - Exact formula now available for measuring scientific success

Scientists develop formula to describe the growth of scientists’ h-index. © treenabeena (from https://eu.fotolia.com/id/84276789)

Polish team has developed equations governing the growth of authors’ h-index using an agent-based model

Scientometrics research is the science of evaluating scientific performance. Physics methods designed to predict growth based on a scale-free network have rarely been applied to this field. Now, scientists in Poland have developed an analytical method using a previously developed agent-based model to predict the h-index, probably the most popular citation-based scientific measurement, using bibliometric data. They are the very first to succeed in developing an exact formula to calculate the number of external citations and self-citations for each paper written by an author. These findings have just been published in EPJ B by Barbara Żogała-Siudem from the Systems Research Institute, Polish Academy of Sciences, Warsaw, and colleagues. It opens the door to applying this growth analysis to social network users or citations from different scientific fields.

Knowing an author's overall number of papers and total number of citations helps compute an approximated value of their h-index, which was named after the American physicist J.E. Hirsch in 2005 and measures the overall number of a scientist's publications as well as their quality and number of citations.

In this study, the authors relied on rate equations, a complex systems physics tool. To establish the equations governing the growth of citation networks, they incorporated a rule called the preferential attachment rule. Although this rule has been known for over 50 years, it remained unclear until now how and why such rules matter to the growth of the h-index. The explanation came from incorporating the rule into agent-based models representing citation networks, otherwise known as the Ionescu-Chopard (IC) model.

This led to exact h-index predictions — just like with the IC model alone — and enabled the authors to explain some underlying bibliometric phenomena. For example, they showed that the h-index can be further investigated using the aggregation theory. Lastly, they verified their results with data from real authors as well as numerical simulations.

This was our first experience of publishing with EPJ Web of Conferences. We contacted the publisher in the middle of September, just one month prior to the Conference, but everything went through smoothly. We have had published MNPS Proceedings with different publishers in the past, and would like to tell that the EPJ Web of Conferences team was probably the best, very quick, helpful and interactive. Typically, we were getting responses from EPJ Web of Conferences team within less than an hour and have had help at every production stage.
We are very thankful to Solange Guenot, Web of Conferences Publishing Editor, and Isabelle Houlbert, Web of Conferences Production Editor, for their support. These ladies are top-level professionals, who made a great contribution to the success of this issue. We are fully satisfied with the publication of the Conference Proceedings and are looking forward to further cooperation. The publication was very fast, easy and of high quality. My colleagues and I strongly recommend EPJ Web of Conferences to anyone, who is interested in quick high-quality publication of conference proceedings.

On behalf of the Organizing and Program Committees and Editorial Team of MNPS-2019, Dr. Alexey B. Nadykto, Moscow State Technological University “STANKIN”, Moscow, Russia. EPJ Web of Conferences vol. 224 (2019)

ISSN: 2100-014X (Electronic Edition)

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