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Uncovering inter-specialty knowledge communication using author citation networks

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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.

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Notes

  1. In fact, the distance from TMLS to CI is just at the threshold of 1.518. If we delete this arc, the division of Fig. 5 will be very similar to that of Fig. 3.

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Acknowledgments

This work is supported by the National Social Science Foundation of China (No. 12CTQ026), the Program for the Top Young Academic Leaders of Higher Learning Institutions of Shanxi (No. 2014052006) and the 131 Leading Talents Project of Colleges and Universities of Shanxi.

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Authors and Affiliations

  1. Institute of Management and Decision, Shanxi University, Taiyuan, 030006, Shanxi, People’s Republic of China

    Ruimin Ma

  2. College of Computing and Informatics, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA

    Erjia Yan

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  1. Ruimin Ma
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Correspondence to Ruimin Ma.

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Ma, R., Yan, E. Uncovering inter-specialty knowledge communication using author citation networks. Scientometrics 109, 839–854 (2016). https://doi.org/10.1007/s11192-016-2091-2

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