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A multi-level network analysis of web-citations among the world’s universities

Author

Listed:
  • George A. Barnett

    (University of California)

  • Han Woo Park

    (Yeungnam University)

  • Ke Jiang

    (University of California)

  • Chuan Tang

    (Chinese Academy of Sciences)

  • Isidro F. Aguillo

    (National Research Council (CSIC))

Abstract

This paper describes the results of a multi-level network analysis of web-citations among the 1,000 universities with the greatest presence on the world wide web. Using data from January 2011, it describes the web-citation network of the world’s universities and ascertains the antecedent factors that determine its structure. At the university level, the network is composed of ten groups, and the most central universities are mainly from the United States. The factors that predict the structure of the network are, whether or not the universities are in the same country, the language of instruction, the size and excellence of the institution (university ranking and the number of Nobel Prizes received), if they offer doctoral degrees, and the infrastructure of its country. Physical distance was not a determinant of the network’s structure. At the nation-state level, international connections among a nation’s universities are composed of a single cluster with the United States, United Kingdom and Germany at the center. The structure of the international network may be predicted by the countries’ overall hyperlink connections, international co-authorships, student flows and the number of Nobel Prizes won by its citizen.

Suggested Citation

  • George A. Barnett & Han Woo Park & Ke Jiang & Chuan Tang & Isidro F. Aguillo, 2014. "A multi-level network analysis of web-citations among the world’s universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 5-26, April.
    • Handle: RePEc:spr:scient:v:99:y:2014:i:1:d:10.1007_s11192-013-1070-0
    DOI: 10.1007/s11192-013-1070-0
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    References listed on IDEAS

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    9. Nicolò Musmeci & Vincenzo Nicosia & Tomaso Aste & Tiziana Di Matteo & Vito Latora, 2017. "The Multiplex Dependency Structure of Financial Markets," Complexity, Hindawi, vol. 2017, pages 1-13, September.

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