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Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers

Author

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  • Vincenza Carchiolo

    (Dipartimento di Ingegneria Elettrica Elettronica Informatica, Università di Catania, Viale Andrea Doria, 9-95127 Catania, Italy)

  • Marco Grassia

    (Dipartimento di Ingegneria Elettrica Elettronica Informatica, Università di Catania, Viale Andrea Doria, 9-95127 Catania, Italy)

  • Michele Malgeri

    (Dipartimento di Ingegneria Elettrica Elettronica Informatica, Università di Catania, Viale Andrea Doria, 9-95127 Catania, Italy)

  • Giuseppe Mangioni

    (Dipartimento di Ingegneria Elettrica Elettronica Informatica, Università di Catania, Viale Andrea Doria, 9-95127 Catania, Italy)

Abstract

The study of the behaviors of large community of researchers and what correlations exist between their environment, such as grouping rules by law or specific institution policies, and their performance is an important topic since it affects the metrics used to evaluate the quality of the research. Moreover, in several countries, such as Italy, these metrics are also used to define the recruitment and funding policies. To effectively study these topics, we created a procedure that allow us to craft a large dataset of Italian Academic researchers, having the most important performance indices together with co-authorships information, mixing data extracted from the official list of academic researchers provided by Italian Ministry of University and Research and the Elsevier’s Scopus database. In this paper, we discuss our approach to automate the process of correct association of profiles and the mapping of publications reducing the use of computational resources. We also present the characteristics of four datasets related to specific research fields defined by the Italian Ministry of University and Research used to group the Italian researchers. Then, we present several examples of how the information extracted from these datasets can help to achieve a better understanding of the dynamics influencing scientist performances.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jftint:v:14:y:2022:i:6:p:187-:d:840167
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    as
    1. Vladimir Batagelj & Matjaž Zaveršnik, 2011. "Fast algorithms for determining (generalized) core groups in social networks," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(2), pages 129-145, July.
    2. Sushil, 2018. "Is Management Science Applicable at the Top Level?," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 1-3, March.
    3. John P A Ioannidis, 2018. "All science should inform policy and regulation," PLOS Medicine, Public Library of Science, vol. 15(5), pages 1-3, May.
    4. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. I. A binary network analysis," Papers 1103.1243, arXiv.org, revised Nov 2011.
    5. Yoshiaki Fujita & Michael S. Vitevitch, 2022. "Using network analyses to examine the extent to which and in what ways psychology is multidisciplinary," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    6. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    7. Tomassini, Marco & Luthi, Leslie, 2007. "Empirical analysis of the evolution of a scientific collaboration network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 750-764.
    8. Zheng Xie, 2021. "A distributed hypergraph model for simulating the evolution of large coauthorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4609-4638, June.
    9. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    10. 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.
    11. Tiziano Squartini & Giorgio Fagiolo & Diego Garlaschelli, 2011. "Randomizing world trade. II. A weighted network analysis," Papers 1103.1249, arXiv.org, revised Nov 2011.
    12. T. S. Evans & R. Lambiotte & P. Panzarasa, 2011. "Community structure and patterns of scientific collaboration in Business and Management," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 381-396, October.
    13. Weihua Li & Tomaso Aste & Fabio Caccioli & Giacomo Livan, 2019. "Early coauthorship with top scientists predicts success in academic careers," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    14. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    15. Anjan Kumar Chandra & Kamalika Basu Hajra & Pratap Kumar Das & Parongama Sen, 2007. "Modeling Temporal And Spatial Features Of Collaboration Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1157-1172.
    16. Massimo Franceschet, 2011. "Collaboration in computer science: A network science approach," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1992-2012, October.
    17. Corrêa Jr., Edilson A. & Silva, Filipi N. & da F. Costa, Luciano & Amancio, Diego R., 2017. "Patterns of authors contribution in scientific manuscripts," Journal of Informetrics, Elsevier, vol. 11(2), pages 498-510.
    18. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
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    1. Silvia Bacci & Bruno Bertaccini & Alessandra Petrucci, 2023. "Insights from the co-authorship network of the Italian academic statisticians," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4269-4303, August.

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