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Register a new userReference Publication Year Spectroscopy (RPYS) in practice: Three RPYS analyzes in the course of Workshop III Cited References Analysis Using CRExplorer at the 18th ISSI conference
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Robin Haunschild
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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In course of the organization of Workshop III entitled Cited References Analysis Using CRExplorer at the International Conference of the International Society for Scientometrics and Informetrics (ISSI2021), we have prepared three reference publication year spectroscopy (RPYS) analyzes: (i) papers published in Journal of Informetrics, (ii) papers regarding the topic altmetrics, and (iii) papers published by Ludo Waltman (we selected this researcher since he received the Derek de Solla Price Memorial Medal during the ISSI2021 conference). The first RPYS analysis has been presented live at the workshop and the second and third RPYS analyzes have been left to the participants for undertaking after the workshop. Here, we present our own results for all three RPYS analyzes so that the participants can compare their results with ours or can additional help from this paper for performing these and other RPYS analyzes on their own. The three RPYS analyzes have shown quite different seminal papers with a few overlaps. Many of the foundational papers in the field of scientometrics (e.g., distributions of publications and citations), citation network and co-citation analyzes, and citation analysis with the aim of impact measurement and research evaluation were retrieved as seminal papers of the papers published in Journal of Informetrics. Mainly papers with discussions of the deficiencies of citation-based impact measurements and comparisons between altmetrics and citations were retrieved as seminal papers of the topic altmetrics. The RPYS analysis of the paper set published by Ludo Waltman mainly retrieved papers about network analyzes, citation relations, and citation impact measurement.
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We have organized Workshop III entitled Cited References Analysis Using CRExplorer at ISSI2021. Here, we report and reflect on this workshop. The aim of this workshop was to bring beginners, practitioners, and experts in cited references analyses together. A mixture of presentations and an interactive part was intended to provide benefits for all kinds of scientometricians with an interest in cited references analyses.
Many studies in information science have looked at the growth of science. In this study, we re-examine the question of the growth of science. To do this we (i) use current data up to publication year 2012 and (ii) analyse it across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data are analysed with an advanced statistical technique - segmented regression analysis - which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (1) The number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (2) the number of cited references in the publications of the source items per cited reference year. We have looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars and 8 to 9% to 2012.
We present a study of active learning pedagogies in an upper division physics course. This work was guided by the principle of deliberate practice for the development of expertise, and this principle was used in the design of the materials and the orchestration of the classroom activities of the students. We present our process for efficiently converting a traditional lecture course based on instructor notes into activities for such a course with active learning methods. Ninety percent of the same material was covered and scores on common exam problems showed a 15 % improvement with an effect size greater than 1 after the transformation. We observe that the improvement and the associated effect size is sustained after handing off the materials to a second instructor. Because the improvement on exam questions was independent of specific problem topics and because the material tested was so mathematically advanced and broad (including linear algebra, Fourier Transforms, partial differential equations, vector calculus), we expect the transformation process could be applied to most upper division physics courses having a similar mathematical base.
Scientometrics studies have extended from direct citations to high-order citations, as simple citation count is found to tell only part of the story regarding scientific impact. This extension is deemed to be beneficial in scenarios like research evaluation, science history modeling, and information retrieval. In contrast to citations of citations (forward citation generations), references of references (backward citation generations) as another side of high-order citations, is relatively less explored. We adopt a series of metrics for measuring the unfolding of backward citations of a focal paper, tracing back to its knowledge ancestors generation by generation. Two sub-fields in Physics are subject to such analysis on a large-scale citation network. Preliminary results show that (1) most papers in our dataset can be traced to their knowledge ancestry; (2) the size distribution of backward citation generations presents a decreasing-and-then-increasing shape; and (3) citations more than one generation away are still relevant to the focal paper, from either a forward or backward perspective; yet, backward citation generations are higher in topic relevance to the paper of interest. Furthermore, the backward citation generations shed lights for literature recommendation, science evaluation, and sociology of science studies.
This paper presents and describes the methodological opportunities offered by bibliometric data to produce indicators of scientific mobility. Large bibliographic datasets of disambiguated authors and their affiliations allow for the possibility of tracking the affiliation changes of scientists. Using the Web of Science as data source, we analyze the distribution of types of mobile scientists for a selection of countries. We explore the possibility of creating profiles of international mobility at the country level, and discuss potential interpretations and caveats. Five countries (Canada, The Netherlands, South Africa, Spain, and the United States) are used as examples. These profiles enable us to characterize these countries in terms of their strongest links with other countries. This type of analysis reveals circulation among and between countries with strong policy implications.
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