The long-term dynamics of co-authorship scientific networks: Iberoamerican countries (1973–2010)
We analyse the national production of academic knowledge in all Iberoamerican and Caribbean countries between 1973 and 2010. We show that the total number of citable scientific publications listed in the Science Citation Index (SCI), the Social Science Citation Index (SSCI) and Arts and Humanities Citation Index (A&HCI) follow an exponential growth, the same as their national productivity (number of publications per capita). During the last 38 years, Portugal shows the highest growth rate in both indicators. We explore the temporal evolution of the co-authorship patterns within a sample of 12 Iberoamerican countries (responsible for 98% of the total regional publications between 1973 and 2010) with a group of 46 other different nations. We show that the scientific co-authorship among countries follows a power-law and behaves as a self-organizing scale-free network, where each country appears as a node and each co-publication as a link. We develop a mathematical model to study the temporal evolution of co-authorship networks, based on a preferential attachment strategy and we show that the number of co-publications among countries grows quadraticly against time. We empirically determine the quadratic growth constants for 352 different co-authorship networks within the period 1973–2006. We corroborate that the connectivity of Iberoamerican countries with larger scientific networks (hubs) is growing faster than that of other less connected countries. We determine the dates, t0, at which the co-authorship connectivities trigger the self-organizing scale-free network for each of the 352 cases. We find that the latter follows a normal distribution around year 1981.4±2.2 and we connect this effect with a brain-drain process generated during the previous decade. We show how the number of co-publications Pki(t) between country k and country i, against the coupling growth-coefficients aki, follows a power-law mathematical relation. We develop a methodology to use the empirically determined growth constants for each co-authorship network to predict changes in the relative intensity of cooperation among countries and we test its predictions for the period 2007–2010. We finally discuss the implications of our findings on the science and technology policies.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Katz, J. Sylvan, 1999. "The self-similar science system1," Research Policy, Elsevier, vol. 28(5), pages 501-517, June.
- 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.
- Wagner, Caroline S. & Leydesdorff, Loet, 2005. "Network structure, self-organization, and the growth of international collaboration in science," Research Policy, Elsevier, vol. 34(10), pages 1608-1618, December.
- Li, Menghui & Wu, Jinshan & Wang, Dahui & Zhou, Tao & Di, Zengru & Fan, Ying, 2007. "Evolving model of weighted networks inspired by scientific collaboration networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 355-364.
- Melin, Goran, 2000. "Pragmatism and self-organization: Research collaboration on the individual level," Research Policy, Elsevier, vol. 29(1), pages 31-40, January.
- Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
- 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.