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.
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References
Batagelj, V., Mrvar, A. (2001), Pajek (Version 0.70) — Program for Large Network Analysis, University of Ljubljana, Slovenia.
Carolyn, J. A., Wasserman, S., Crouch, B. (1999), A p* primer: logit models for social networks, Social Networks, 21: 37–66.
Farahat, H. (2002), Authorship patterns in agricultural sciences in Egypt, Scientometrics, 55(2): 157–170.
Koku, E., Nazer, N., Wellman, B. (2001), Netting scholars: online and offline, American Behavioral Scientist, 44: 1750–1772.
Liang, L., Guo, Y., Davis, M. (2002), Collaborative patterns and age structures in Chinese publications, Scientometrics, 54(3): 473–489.
Liberman, S., Wolf, K. B. (1997), The flow of knowledge: scientific contacts in formal meetings, Social Networks, 19: 271–283.
Melin, G., Persson, O. (1996), Studying research collaboration using co-authorship, Scientometrics, 36(3): 363–377.
Nagpaul, P. S. (2002), Visualizing cooperation networks of elite institutions in India, Scientometrics, 54(2) 213–228.
Newman, M. E. J. (2003), Ego-centered networks and the ripple effect, Social Networks, 25: 83–95.
Rivellini, G., Rizzi, E. (2002), Science network in Italian population research: an application of social network analysis, Atti della XLI Riunione Scientifica, Società Italiana di Statistica, CLEUP, Padova: pp. 215–218.
Snijders, T. A. B. (2001), The statistical evaluation of social network dynamics, In: M. E. Sobel, M. P. Becker (Eds), Sociological Methodology, Boston and London, Basil Blackwell.
Snijders, T. A. B. (2002), Markov Chain Monte Carlo estimation of exponential random graph models, Journal of Social Structure, 3: 2.
Wasserman, S., Pattison, P. (1996), Logit models and logistic regression for social networks: I. An introduction to Markov graphs and p*, Psychometrika, 61: 401–426.
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Rivellini, G., Rizzi, E. & Zaccarin, S. The science network in Italian population research: An analysis according to the social network perspective. Scientometrics 67, 407–418 (2006). https://doi.org/10.1556/Scient.67.2006.3.5
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DOI: https://doi.org/10.1556/Scient.67.2006.3.5