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Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field

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  • Yue, Zenghui
  • Xu, Haiyun
  • Yuan, Guoting
  • Pang, Hongshen

Abstract

Knowledge diffusion based on scientific collaboration is similar to disease propagation through actual contact. Inspired by the disease-spreading model in complex networks, this study classifies the states of research entities during the process of knowledge diffusion in scientific collaboration into four categories. Research entities can transform from one state to another with a certain probability, which results in the evolution rules of knowledge diffusion in scientific collaboration networks. The knowledge diffusion model of differential dynamics in scientific collaboration of non-uniformity networks is formed, and the relationship between the degree distribution and evolution of knowledge diffusion is further discussed, to reveal the dynamic mechanics of knowledge diffusion in scientific collaboration networks. Finally, an empirical analysis is conducted on knowledge diffusion in an institutional scientific collaboration network by taking the graphene field as an example. The results show that the state evolution of research entities in the knowledge diffusion process of scientific collaboration networks is affected not only by the evolution states of adjacent research entities with whom they have certain collaboration relationships, but also by the structural attributes and degree distributions of scientific collaboration networks. The evolution of knowledge diffusion in scientific collaboration entities with different degrees also shows different trends.

Suggested Citation

  • Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
  • Handle: RePEc:eee:phsmap:v:524:y:2019:i:c:p:375-391
    DOI: 10.1016/j.physa.2019.04.201
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    as
    1. Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
    2. Chaomei Chen & Diana Hicks, 2004. "Tracing knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 199-211, February.
    3. Justel, Ana & Peña, Daniel & Zamar, Rubén, 1997. "A multivariate Kolmogorov-Smirnov test of goodness of fit," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 251-259, October.
    4. Corinne Autant‐Bernard & Jacques Mairesse & Nadine Massard, 2007. "Spatial knowledge diffusion through collaborative networks," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 341-350, August.
    5. Torben Klarl, 2014. "Knowledge diffusion and knowledge transfer revisited: two sides of the medal," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 737-760, September.
    6. Lin, Min & Li, Nan, 2010. "Scale-free network provides an optimal pattern for knowledge transfer," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 473-480.
    7. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.
    8. EunKyung Chung & Nahyun Kwon & Jungyeoun Lee, 2016. "Understanding scientific collaboration in the research life cycle: Bio- and nanoscientists' motivations, information-sharing and communication practices, and barriers to collaboration," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(8), pages 1836-1848, August.
    9. Louis Y. Y. Lu & John S. Liu, 2013. "An innovative approach to identify the knowledge diffusion path: the case of resource-based theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 225-246, January.
    10. Jasjit Singh, 2005. "Collaborative Networks as Determinants of Knowledge Diffusion Patterns," Management Science, INFORMS, vol. 51(5), pages 756-770, May.
    11. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    12. Erjia Yan, 2014. "Finding knowledge paths among scientific disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(11), pages 2331-2347, November.
    13. Wang, Jiang-Pan & Guo, Qiang & Yang, Guang-Yong & Liu, Jian-Guo, 2015. "Improved knowledge diffusion model based on the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 250-256.
    14. Piergiuseppe Morone & Richard Taylor, 2004. "Knowledge diffusion dynamics and network properties of face-to-face interactions," Journal of Evolutionary Economics, Springer, vol. 14(3), pages 327-351, July.
    15. Yang, Guang-Yong & Hu, Zhao-Long & Liu, Jian-Guo, 2015. "Knowledge diffusion in the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 429-436.
    16. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    17. Erjia Yan, 2016. "Disciplinary knowledge production and diffusion in science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2223-2245, September.
    18. Hamidreza Eslami & Ashkan Ebadi & Andrea Schiffauerova, 2013. "Effect of collaboration network structure on knowledge creation and technological performance: the case of biotechnology in Canada," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 99-119, October.
    19. Liu, Yuxian & Rousseau, Ronald & Guns, Raf, 2013. "A layered framework to study collaboration as a form of knowledge sharing and diffusion," Journal of Informetrics, Elsevier, vol. 7(3), pages 651-664.
    20. Xiao, Yu & Lu, Louis Y.Y. & Liu, John S. & Zhou, Zhili, 2014. "Knowledge diffusion path analysis of data quality literature: A main path analysis," Journal of Informetrics, Elsevier, vol. 8(3), pages 594-605.
    21. Ming-yueh Tsay, 2015. "Knowledge flow out of the domain of information science: a bibliometric and citation analysis study," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 487-502, January.
    22. Olle Persson & Wolfgang Glänzel & Rickard Danell, 2004. "Inflationary bibliometric values: The role of scientific collaboration and the need for relative indicators in evaluative studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 421-432, August.
    23. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    24. Jonathan Adams, 2013. "The fourth age of research," Nature, Nature, vol. 497(7451), pages 557-560, May.
    25. Su, Qiang & Huang, Jiajia & Zhao, Xiande, 2015. "An information propagation model considering incomplete reading behavior in microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 55-63.
    26. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.
    27. Yongjun Zhu & Erjia Yan, 2015. "Dynamic subfield analysis of disciplines: an examination of the trading impact and knowledge diffusion patterns of computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 335-359, July.
    28. Xuezhao Wang & Yajuan Zhao & Rui Liu & Jing Zhang, 2013. "Knowledge-transfer analysis based on co-citation clustering," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 859-869, December.
    29. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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    6. Zenghui Yue & Haiyun Xu & Guoting Yuan & Yan Qi, 2022. "Modeling knowledge diffusion in the disciplinary citation network based on differential dynamics," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7593-7613, December.

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