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The science network in Italian population research: An analysis according to the social network perspective

Author

Listed:
  • Giulia Rivellini

    (Università Cattolica del Sacro Cuore)

  • Ester Rizzi

    (Università Cattolica del Sacro Cuore)

  • Susanna Zaccarin

    (University of Trieste)

Abstract

The scientific community organises its relationships into network patterns, where the nodes are individuals (scientists) and the links are acquaintance and common work, usually presented at workshops and conferences and/or published in books and scientific journals. A references review on Population Studies by Italian scientists is delivered every two years by the Demography Section of the Italian Statistical Society; the review is exhaustive for academic demographers. In this paper, the properties of the demographers’ network in 1998–1999 are evaluated, with the aim of identifying factors which may influence collaborative relations among actors. The probability of cooperation between couples (dyads) of demographers is modelled, conditionally on observed characteristics of the dyad (sex, academic position, university affiliation). Main results suggest that “closeness”, defined in a wider sense and not simply as geographical proximity, plays a major role in determining actors’ relationships.

Suggested Citation

  • Giulia Rivellini & Ester Rizzi & Susanna Zaccarin, 2006. "The science network in Italian population research: An analysis according to the social network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 407-418, June.
    • Handle: RePEc:spr:scient:v:67:y:2006:i:3:d:10.1556_scient.67.2006.3.5
    DOI: 10.1556/Scient.67.2006.3.5
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    References listed on IDEAS

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    1. Hashem Farahat, 2002. "Authorship patterns in agricultural sciences in Egypt," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 157-170, August.
    2. Liming Liang & Yongzheng Guo & Mari Davis, 2002. "Collaborative patterns and age structures in Chinese publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 473-489, July.
    3. P. S. Nagpaul, 2002. "Visualizing cooperation networks of elite institutions in India," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 213-228, June.
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    Cited by:

    1. Luigi Aldieri & Gennaro Guida & Maxim Kotsemir & Concetto Paolo Vinci, 2019. "An investigation of impact of research collaboration on academic performance in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2003-2040, July.
    2. Viviana Egidi & Michele Antonio Salvatore & Giulia Rivellini & Silvia D'Angelo, 2018. "A network approach to studying cause-of-death interrelations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(16), pages 373-400.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo & Gianluca Murgia, 2014. "Variation in research collaboration patterns across academic ranks," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2275-2294, March.
    4. Francesca DE BATTISTI & Silvia SALINI, 2011. "Robust analysis of bibliometric data," Departmental Working Papers 2011-36, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    5. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "Gender differences in research collaboration," Journal of Informetrics, Elsevier, vol. 7(4), pages 811-822.
    6. Francesca De Battisti & Silvia Salini, 2013. "Robust analysis of bibliometric data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 269-283, June.
    7. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2019. "A gender analysis of top scientists’ collaboration behavior: evidence from Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 405-418, August.

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