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Uncovering inter-specialty knowledge communication using author citation networks

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  • Ruimin Ma

    (Shanxi University)

  • Erjia Yan

    (Drexel University)

Abstract

Knowledge communication plays a fundamental role in studies of science of science. This paper aims to examine inter-specialty communication patterns within a discipline using author citation networks. Two metrics are designed, including average knowledge flow and average shortest distance. They are used to identify the impact and diffusion characteristics of inter-specialty knowledge communication. We apply these metrics to an empirical data set of Chinese library and information science (CLIS) publications. We find that the two metrics portray different aspects of knowledge communication in CLIS and conclude that indirect paths, the size of specialties, and the communication structure among specialties may lead to the differences.

Suggested Citation

  • Ruimin Ma & Erjia Yan, 2016. "Uncovering inter-specialty knowledge communication using author citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 839-854, November.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:2:d:10.1007_s11192-016-2091-2
    DOI: 10.1007/s11192-016-2091-2
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