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Diffusion of nanotechnology knowledge in Turkey and its network structure


  • Hamid Darvish

    (Kastamonu University)

  • Yaşar Tonta

    (Hacettepe University)


This paper aims to assess the diffusion and adoption of nanotechnology knowledge within the Turkish scientific community using social network analysis and bibliometrics. We retrieved a total of 10,062 records of nanotechnology papers authored by Turkish researchers between 2000 and 2011 from Web of Science and divided the data set into two 6-year periods. We analyzed the most prolific and collaborative authors and universities on individual, institutional and international levels based on their network properties (e.g., centrality) as well as the nanotechnology research topics studied most often by the Turkish researchers. We used co-word analysis and mapping to identify the major nanotechnology research fields in Turkey on the basis of the co-occurrence of words in the titles of papers. We found that nanotechnology research and development in Turkey is on the rise and its diffusion and adoption have increased tremendously thanks to the Turkish government’s decision a decade ago identifying nanotechnology as a strategic field and providing constant support since then. Turkish researchers tend to collaborate within their own groups or universities and the overall connectedness of the network is thus low. Their publication and collaboration patterns conform to Lotka’s law. They work mainly on nanotechnology applications in Materials Sciences, Chemistry and Physics, among others. This is commensurate, more or less, with the global trends in nanotechnology research and development.

Suggested Citation

  • Hamid Darvish & Yaşar Tonta, 2016. "Diffusion of nanotechnology knowledge in Turkey and its network structure," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 569-592, May.
  • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1854-0
    DOI: 10.1007/s11192-016-1854-0

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    References listed on IDEAS

    1. Leydesdorff, Loet & Welbers, Kasper, 2011. "The semantic mapping of words and co-words in contexts," Journal of Informetrics, Elsevier, vol. 5(3), pages 469-475.
    2. Chen, Chaomei & Chen, Yue & Horowitz, Mark & Hou, Haiyan & Liu, Zeyuan & Pellegrino, Donald, 2009. "Towards an explanatory and computational theory of scientific discovery," Journal of Informetrics, Elsevier, vol. 3(3), pages 191-209.
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    Cited by:

    1. Hao Wang & Sanhong Deng & Xinning Su, 2016. "A study on construction and analysis of discipline knowledge structure of Chinese LIS based on CSSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1725-1759, December.
    2. Carlos Olmeda-Gómez & Carlos Romá-Mateo & Maria-Antonia Ovalle-Perandones, 2019. "Overview of trends in global epigenetic research (2009–2017)," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1545-1574, June.
    3. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.

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