Combining referenced publication year spectroscopy and topic clustering to identify key knowledge foundations in scientometrics: an analysis of recipients of the Price Award

Wei Cheng, Dejun Zheng (), Xiaomin Zheng and Huanhuan Ni
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Wei Cheng: Nanjing Agriculture University
Dejun Zheng: Nanjing Agriculture University
Xiaomin Zheng: Nanjing Agriculture University
Huanhuan Ni: Nanjing Agriculture University

Scientometrics, 2025, vol. 130, issue 2, No 22, 1077-1099

Abstract: Abstract Identifying key knowledge foundation is a significant branch of citation analysis. The identification of key knowledge foundations and visualization of their knowledge dissemination maps are pivotal in understanding the development and dynamics of scientific fields. While the referenced publication year spectroscopy (RPYS) analysis method can elucidate the historical roots and significant papers within a knowledge domain, it cannot effectively depict the thematic content of these historical works. Consequently, this study employs the field of scientometrics as a case study to propose a novel approach that integrates RPYS and topic clustering techniques for the identification and analysis of key knowledge foundations. Utilizing publication data and references from recipients of the prestigious Price Award in the field of scientometrics as representative samples, we identified 303 key references along with 5832 unduplicated citation records, encompassing a total of 2109 unduplicated papers. Subsequently, we employed topic clustering to construct a topic citation network comprising 40 distinct topics. This study offers a comprehensive analysis of key knowledge foundations in scientometrics through an overall analysis, temporal stage analysis, and scholar-specific analysis of the topic citation network. Our findings illuminate classic topics that have significantly contributed to the development of scientometrics, the evolution of key knowledge foundations over time, and the unique impacts of individual scholars. This study underscores the interconnectedness of research themes while highlighting the enduring influence of foundational research. This approach not only establishes a robust framework for identifying and analyzing key knowledge foundations in scientometrics but also serves as a valuable reference for identifying and evaluating key knowledge foundations across other research fields.

Keywords: Scientometrics; Key knowledge foundations; RPYS; Semantic clustering; Sentence-BERT; Kmeans; Citation analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11192-025-05230-4

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