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Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion

Author

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  • Ji-ping Gao

    (Institute of Science Studies and S&T Management and WISE Lab, Dalian University of Technology)

  • Kun Ding

    (Institute of Science Studies and S&T Management and WISE Lab, Dalian University of Technology)

  • Li Teng

    (Institute of Science Studies and S&T Management and WISE Lab, Dalian University of Technology)

  • Jie Pang

    (Institute of Science Studies and S&T Management and WISE Lab, Dalian University of Technology)

Abstract

The paper presents a methodology called hybrid documents co-citation analysis, for studying the interaction between science and technology in technology diffusion. Our approach rests mostly on patent citation, cluster analysis and network analysis. More specifically, with the patents citing Smalley RE in Derwent innovations index as the data sets, the paper implemented hybrid documents co-citation network through two procedures. Then spectrum cluster algorithm was used to reveal the knowledge structure in technology diffusion. After that, with the concordance between network properties and technology diffusion mechanisms, three indicators containing degree, betweenness and citation half-life, were calculated to discuss the basic documents in the pivotal position during the technology diffusion. At last, the paper summarized the hybrid documents co-citation analysis in practise, thus concluded that science and technology undertook different functions and acted dominatingly in the different period of technology diffusion, though they were co-activity all the time.

Suggested Citation

  • Ji-ping Gao & Kun Ding & Li Teng & Jie Pang, 2012. "Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 459-471, November.
    • Handle: RePEc:spr:scient:v:93:y:2012:i:2:d:10.1007_s11192-012-0691-z
    DOI: 10.1007/s11192-012-0691-z
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    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 577-598.
    3. Chaomei Chen & Jian Zhang & Michael S. Vogeley, 2010. "Making sense of the evolution of a scientific domain: a visual analytic study of the Sloan Digital Sky Survey research," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 669-688, June.
    4. Sujit Bhattacharya & Hildrun Kretschmer & Martin Meyer, 2003. "Characterizing intellectual spaces between science and technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(2), pages 369-390, October.
    5. Stolpe, Michael, 2002. "Determinants of knowledge diffusion as evidenced in patent data: the case of liquid crystal display technology," Research Policy, Elsevier, vol. 31(7), pages 1181-1198, September.
    6. Chaomei Chen & Fidelia Ibekwe-SanJuan & Jianhua Hou, 2010. "The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1386-1409, July.
    7. Janghyeok Yoon & Kwangsoo Kim, 2011. "Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 213-228, July.
    8. Hyun Woo Park & Jay Kang, 2009. "Patterns of scientific and technological knowledge flows based on scientific papers and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 811-820, December.
    9. Narin, Francis & Hamilton, Kimberly S. & Olivastro, Dominic, 1997. "The increasing linkage between U.S. technology and public science," Research Policy, Elsevier, vol. 26(3), pages 317-330, October.
    10. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    11. M. Meyer & K. Debackere & W. Glänzel, 2010. "Can applied science be ‘good science’? Exploring the relationship between patent citations and citation impact in nanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(2), pages 527-539, November.
    12. Angela Hullmann & Martin Meyer, 2003. "Publications and patents in nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 507-527, November.
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