Co-Citation Network of Articles in the field of Nuclear Sciences and Technology

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Daniali Samira; Riahinia Nosrat; Nourmohammadi Hamzehali; Azimi Ali; Safarzadeh Omid

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

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Journal: Scientometrics Research Journal Year:2024 | Volume: | Issue: Page(s): 181-202

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Information Journal Paper

Title

Co-Citation Network of Articles in the field of Nuclear Sciences and Technology

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Keywords

ScientometricsQ4

documents co-citationQ4

Science MapQ4

citespaceQ4

Nuclear sciencesQ4

and technologyQ4

Abstract

Purpose: The purpose of the current research is to identify the subject trends in the co-citation network of prominent documents in the field of nuclear science and technology worldwide. Analyzing various scientific fields can assist researchers in understanding the limits and boundaries of science. Furthermore, mapping and analyzing the structure of science can serve as a guide for researchers and policymakers in different scientific fields to identify research priorities and tailor them to the specific needs of their country.Methodology: The current research is practical in terms of purpose. Initially, Scientometrics techniques were utilized to analyze the subject area of nuclear science and technology. Subsequently, the results from the Scientometrics segment of the research were scrutinized through interviews with subject matter experts. The statistical population of the research included all the documents published in the core collection of the science website in the field of nuclear science and technology (342,425 documents) for the quantitative part. For the analysis and creation of a scientific map, notable articles in the field of nuclear science and technology (40,835 articles) that received over 25 citations from 1972 to 2021 were considered. In the qualitative part of the research, a panel of 13 experts specializing in this field was formed. citespace software was employed to analyze and create co-citation maps of notable documents in the field of nuclear science and technology. To examine the evolution in the field of nuclear science and technology from 1972 to 2021, a 50-year timeframe was divided into five ten-year intervals. Subsequently, the top 50 nodes' threshold for each of the 10-year time frames was selected using the trial-and-error method. Findings: The results of the research showed that among the 205 countries participating in the production of articles in the field of nuclear science and technology, the United States of America produced 84,359 scientific papers. The magazine Nuclear Instruments Methods in Physics Research Section Accelerators, Spectrometers, Detectors, and Associated Equipment produced 46,547 articles. Scientifically, the United States of America Energy Agency ranked first by producing 33,943 scientific degrees. The subject area of nuclear science technology, with 336,489 scientific degrees, is considered a pioneer in the production of scientific degrees in this field. The co-citation network of documents in global dimensions formed 57 thematic clusters. The results of the co-citation analysis of articles in global dimensions showed that Cluster #0 and Cluster #1, both with 29 members, are the largest subject clusters formed from 1972 to 2021. The average year of formation of Cluster #0 is 1978, and the dominant topic of this cluster is computer studies and profiles. The next important cluster is Cluster #1, formed in 2018, making it the newest cluster in the field of nuclear science and technology. The topic of this cluster is deep learning and its application in Nuclear sciences. The largest number of clusters (15 out of 57) was formed in the last period, 2012-2021, indicating the special attention of world researchers to various topics in the field of nuclear science and technology. Conclusion: The increasing number of published articles and the upward trend of publications in the field of nuclear science and technology each year underscore the significance and value of this subject area. Research indicates that nuclear science and technology find applications in various disciplines such as physics, chemistry, medicine, medical imaging, and geology. The emergence of thematic clusters like radiation medicine and medical imaging demonstrates the diverse topics and varied applications of nuclear science and technology across different research domains. The establishment of clusters focusing on deep learning in Nuclear sciences further highlights the relevance of this field and its advancements in alignment with modern technological developments.

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