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Author bibliographic coupling analysis: A test based on a Chinese academic database

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  • Ma, Ruimin

Abstract

The paper first introduces the basic problems of author bibliographic coupling including the relationship between author bibliographic coupling and document bibliographic coupling as well as the three calculation methods of author coupling strength, namely, simple method, minimum method and combined method. Next I choose a small sample of authors in Chinese library and information science (LIS) as the research objects to have a comparative analysis of three types of author coupling strength algorithms (the data source is from the Chinese Social Sciences Citation Index (CSSCI)). The result shows that the minimum method is the most appropriate one to calculate the author coupling strength. Then a large sample of authors is chosen to analyze the intellectual structure of Chinese LIS. The result shows that author bibliographic coupling analysis (ABCA) can discover the intellectual structure of a discipline better. It is also found that compared with author cocitation analysis (ACA), ABCA has the advantage that it not only can discover the intellectual structure of a discipline more comprehensively and concretely but also can reflect the research frontier of the discipline. Finally, some practical problems that arise during this research are discussed.

Suggested Citation

  • Ma, Ruimin, 2012. "Author bibliographic coupling analysis: A test based on a Chinese academic database," Journal of Informetrics, Elsevier, vol. 6(4), pages 532-542.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:4:p:532-542
    DOI: 10.1016/j.joi.2012.04.006
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    Cited by:

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    5. García-Lillo, Francisco & Seva-Larrosa, Pedro & Sánchez-García, Eduardo, 2024. "On the basis of research on ‘green’ in the disciplines of management and business," Journal of Business Research, Elsevier, vol. 172(C).
    6. Wang, Qi & Sandström, Ulf, 2014. "Defining the Role of Cognitive Distance in the Peer Review Process: Explorative Study of a Grant Scheme in Infection Biology," INDEK Working Paper Series 2014/10, Royal Institute of Technology, Department of Industrial Economics and Management.
    7. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    8. Ali Gazni & Fereshteh Didegah, 2016. "The relationship between authors’ bibliographic coupling and citation exchange: analyzing disciplinary differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 609-626, May.
    9. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.
    10. Tian, Yunpei & Li, Gang & Mao, Jin, 2023. "Predicting the evolution of scientific communities by interpretable machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    11. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    12. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    13. Prathap, Gangan & Ujum, Ephrance Abu & Kumar, Sameer & Ratnavelu, Kuru, 2021. "Scoring the resourcefulness of researchers using bibliographic coupling patterns," Journal of Informetrics, Elsevier, vol. 15(3).
    14. Tsung-Ming Hsiao & Kuang-hua Chen, 2020. "The dynamics of research subfields for library and information science: an investigation based on word bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 717-737, October.
    15. Jiang Li & Yueting Li, 2015. "Patterns and evolution of coauthorship in China’s humanities and social sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 1997-2010, March.
    16. Song Yanhui & Wu Lijuan & Qiu Junping, 2021. "A comparative study of first and all-author bibliographic coupling analysis based on Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1125-1147, February.
    17. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).

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