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Citation regression analysis of computer science publications in different ranking categories and subfields

Author

Listed:
  • Yifan Qian

    (Beihang University
    Beihang University)

  • Wenge Rong

    (Beihang University
    Beihang University)

  • Nan Jiang

    (Beihang University)

  • Jie Tang

    (Tsinghua University)

  • Zhang Xiong

    (Beihang University
    Beihang University)

Abstract

A number of bibliometric studies point out that the role of conference publications in computer science differs from that in other traditional fields. Thus, it is interesting to identify the relative status of journal and conference publications in different subfields of computer science based on the citation rates categorised by the China Computer Federation (CCF) classifications and venue types. In this research, we construct a dataset containing over 100,000 papers recommended by the CCF catalogue and their citation information. We also investigate some other factors that often influence a paper’s citation rate. An experimental study shows that the relative status of journals and conferences varies greatly in different subfields of computer science, and the impact of different publication levels varies according to the citation rate. We also verify that the classification of a publication, number of authors, maximum h-index of all authors of a paper, and average number of papers published by a publication have different effects on the citation rate, although the citation rate may have a different degree of correlation with these factors.

Suggested Citation

  • Yifan Qian & Wenge Rong & Nan Jiang & Jie Tang & Zhang Xiong, 2017. "Citation regression analysis of computer science publications in different ranking categories and subfields," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1351-1374, March.
    • Handle: RePEc:spr:scient:v:110:y:2017:i:3:d:10.1007_s11192-016-2235-4
    DOI: 10.1007/s11192-016-2235-4
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    3. Cristina López-Duarte & Marta M. Vidal-Suárez & Belén González-Díaz, 2019. "Cross-national distance and international business: an analysis of the most influential recent models," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 173-208, October.
    4. Xiancheng Li & Wenge Rong & Haoran Shi & Jie Tang & Zhang Xiong, 2018. "The impact of conference ranking systems in computer science: a comparative regression analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 879-907, August.
    5. Arash Moghadasi, 2024. "Do SMEs Consider Open Data as a Vital Intellectual Asset? a Systematic Literature Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11784-11818, September.
    6. Jaroslav Fiala & Jiří J. Mareš & Jaroslav Šesták, 2017. "Reflections on how to evaluate the professional value of scientific papers and their corresponding citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 697-709, July.
    7. Nunkoo, Robin & Hall, C. Michael & Rughoobur-Seetah, Soujata & Teeroovengadum, Viraiyan, 2019. "Citation practices in tourism research: Toward a gender conscientious engagement," Annals of Tourism Research, Elsevier, vol. 79(C).
    8. Pilar Valderrama & Manuel Escabias & Evaristo Jiménez-Contreras & Mariano J. Valderrama & Pilar Baca, 2018. "A mixed longitudinal and cross-sectional model to forecast the journal impact factor in the field of Dentistry," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1203-1212, August.
    9. Pilar Valderrama & Evaristo Jiménez-Contreras & Manuel Escabias & Mariano J. Valderrama, 2022. "Introducing a bibliometric index based on factor analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 509-522, January.
    10. Meho, Lokman I., 2019. "Using Scopus’s CiteScore for assessing the quality of computer science conferences," Journal of Informetrics, Elsevier, vol. 13(1), pages 419-433.
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