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Analysis of scientific collaboration network of Italian Institute of Technology

Author

Listed:
  • Enrico di Bella

    (University of Genoa)

  • Luca Gandullia

    (University of Genoa)

  • Sara Preti

    (University of Genoa
    Italian Institute of Technology (IIT))

Abstract

It has been proven that collaboration between authors leads to a positive influence on research. This paper aims to analyse the complex structure of the co-authorship network among researchers of the Italian Institute of Technology. In this paper, we examine two different co-authorship networks created starting from the data of the papers published by the Italian Institute of Technology during the period 2006–2019. We apply the main Social Network Analysis techniques to describe the relational structure of the group of researchers and its evolution over time. The structure and characteristics of the networks are analysed both at macro and micro levels, and an attempt is made to identify a possible relationship between the position of researchers in the graphs and their scientific productivity and quality.

Suggested Citation

  • Enrico di Bella & Luca Gandullia & Sara Preti, 2021. "Analysis of scientific collaboration network of Italian Institute of Technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8517-8539, October.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:10:d:10.1007_s11192-021-04120-9
    DOI: 10.1007/s11192-021-04120-9
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    References listed on IDEAS

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    Cited by:

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    2. Vincenza Carchiolo & Marco Grassia & Michele Malgeri & Giuseppe Mangioni, 2022. "Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers," Future Internet, MDPI, vol. 14(6), pages 1-15, June.
    3. Kristofer Rolf Söderström, 2023. "The structure and dynamics of instrument collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3581-3600, June.
    4. Fan, Lingxu & Guo, Lei & Wang, Xinhua & Xu, Liancheng & Liu, Fangai, 2022. "Does the author’s collaboration mode lead to papers’ different citation impacts? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 16(4).
    5. Marcelo Oliveira Passos & Priscila Lujan Gonzalez & Mathias Schneid Tessmann & Daniel Abreu Pereira Uhr, 2022. "The greatest co-authorships of finance theory literature (1896–2006): scientometrics based on complex networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5841-5862, October.

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