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Exploring prestigious citations sourced from top universities in bibliometrics and altmetrics: a case study in the computer science discipline

Author

Listed:
  • Feiheng Luo

    (Nanyang Technological University)

  • Aixin Sun

    (Nanyang Technological University)

  • Mojisola Erdt

    (Nanyang Technological University)

  • Aravind Sesagiri Raamkumar

    (Nanyang Technological University)

  • Yin-Leng Theng

    (Nanyang Technological University)

Abstract

Citation count is an important indicator for measuring research outputs. There have been numerous studies that have investigated factors affecting citation counts from the perspectives of cited papers and citing papers. In this paper, we focused specifically on citing papers and explored citations sourced from prestigious affiliations in the computer science discipline. The QS World University Rankings was employed to identify prestigious citations, named QS citations. We used the Microsoft Academic Graph, a massive scholarly dataset, and conducted different kinds of analysis between papers with QS citations and those without QS citations. We discovered that papers with QS citations are generally associated with higher total citation counts than those without QS citations. We extended the analysis to authors and journals, and the results indicated that when authors or journals have higher proportions of papers with QS citations, they are usually associated with higher values of the H-index or the Journal Impact Factor respectively. Additionally, papers with QS citations are also associated with a higher Altmetric Attention Score and a higher number of specific types of altmetrics such as tweet counts.

Suggested Citation

  • Feiheng Luo & Aixin Sun & Mojisola Erdt & Aravind Sesagiri Raamkumar & Yin-Leng Theng, 2018. "Exploring prestigious citations sourced from top universities in bibliometrics and altmetrics: a case study in the computer science discipline," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 1-17, January.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:1:d:10.1007_s11192-017-2571-z
    DOI: 10.1007/s11192-017-2571-z
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    1. A. Ferrer-Sapena & E. Erdogan & E Jiménez-Fernández & E. A. Sánchez-Pérez & F. Peset, 2020. "Self-defined information indices: application to the case of university rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2443-2456, September.
    2. Yitong Chen & Keye Wu & Yue Li & Jianjun Sun, 2023. "Impacts of inter-institutional mobility on scientific performance from research capital and social capital perspectives," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3473-3506, June.
    3. Massucci, Francesco Alessandro & Docampo, Domingo, 2019. "Measuring the academic reputation through citation networks via PageRank," Journal of Informetrics, Elsevier, vol. 13(1), pages 185-201.
    4. Jane Cho, 2021. "Altmetrics analysis of highly cited academic papers in the field of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7623-7635, September.
    5. Mingyang Wang & Jiaqi Zhang & Shijia Jiao & Xiangrong Zhang & Na Zhu & Guangsheng Chen, 2020. "Important citation identification by exploiting the syntactic and contextual information of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2109-2129, December.

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