SCIENTIFIC COLLABORATION NETWORK OF ACADEMICIANS IN METU

Year 2016, Volume: 4 , 329 - 335, 01.09.2016

İlker Türker Fatih Gökçe Serhat Orkun Tan

Abstract

:
Scientific collaboration networks (SCNs) are web-like structures generated by
collaborating patterns between scientists. Every co-authoring activity
corresponds to a link between authors in such a network. Being successful
prototypes of evolving complex networks, SCNs display the generic properties of
self-organizing structures including social networks, in an aspect mirroring
the scientific activities of the authors also. Collecting the scientific
collaboration data of Middle East Technical University (METU) from Web of
Science, we constructed a SCN spanning the years 1980 to 2015. Performing the
network analysis procedures, we calculated the network parameters like average
separation, average degree, degree distribution, average clustering coefficient
etc. We outlined that the SCN of METU shows small-world and scale-free
properties, also having high clustering between scientists.

Keywords

Complex networks, scientific collaboration networks, scale-free networks, small-world

References

• Albert, R., & Barabasi, A. L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47-97. doi: 10.1103/RevModPhys.74.47 Amaral, L. A. N., Scala, A., Barthelemy, M., & Stanley, H. E. (2000). Classes of small-world networks. Proceedings of the National Academy of Sciences of the United States of America, 97(21), 11149-11152. doi: 10.1073/pnas.200327197 Barabási, A. L. (2016). Network Science. Cambridge: Cambridge University Press. Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512. doi: 10.1126/science.286.5439.509 Barabasi, A. L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica a-Statistical Mechanics and Its Applications, 311(3-4), 590-614. doi: 10.1016/s0378-4371(02)00736-7 Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. Paper presented at the International AAAI Conference on Weblogs and Social Media, San Jose, California. Cavusoglu, A., & Turker, I. (2013). Scientific collaboration network of Turkey. Chaos Solitons & Fractals, 57, 9-18. doi: 10.1016/j.chaos.2013.07.022 Cavusoglu, A., & Turker, I. (2014). Patterns of collaboration in four scientific disciplines of the Turkish collaboration network. Physica a-Statistical Mechanics and Its Applications, 413, 220-229. doi: 10.1016/j.physa.2014.06.069 Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009). Power-Law Distributions in Empirical Data. Siam Review, 51(4), 661-703. doi: 10.1137/070710111 Ferligoj, A., Kronegger, L., Mali, F., Snijders, T. A. B., & Doreian, P. (2015). Scientific collaboration dynamics in a national scientific system. Scientometrics, 104(3), 985-1012. doi: 10.1007/s11192-015-1585-7 Hoekman, J., Frenken, K., & Tijssen, R. J. W. (2010). Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe. Research Policy, 39(5), 662-673. doi: 10.1016/j.respol.2010.01.012 Leicht, E. A., & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11). doi: 10.1103/PhysRevLett.100.118703 Luzar, B., Levnajic, Z., Povh, J., & Perc, M. (2014). Community Structure and the Evolution of Interdisciplinarity in Slovenia's Scientific Collaboration Network. Plos One, 9(4), 5. doi: 10.1371/journal.pone.0094429 Ma, H. T., Fang, C. L., Pang, B., & Li, G. D. (2014). The Effect of Geographical Proximity on Scientific Cooperation among Chinese Cities from 1990 to 2010. Plos One, 9(11), 11. doi: 10.1371/journal.pone.0111705 METU. (2016). About METU. from http://www.metu.edu.tr/history Milgram, S. (1967). The small-world problem. Psychology Today, 1(1), 61-67. Newman, M. E. J. (2001a). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64(1), 8. Newman, M. E. J. (2001b). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 7. Newman, M. E. J. (2001c). The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 404-409. doi: 10.1073/pnas.021544898 Newman, M. E. J. (2003). The structure and function of complex networks. Siam Review, 45(2), 167-256. doi: 10.1137/s003614450342480 Newman, M. E. J. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America, 101, 5200-5205. doi: 10.1073/pnas.0307545100 Perc, M. (2010). Growth and structure of Slovenia's scientific collaboration network. Journal of Informetrics, 4(4), 475-482. doi: 10.1016/j.joi.2010.04.003 Vazquez, A. (2003). Growing network with local rules: Preferential attachment, clustering hierarchy, and degree correlations. Physical Review E, 67(5), 15. doi: 10.1103/PhysRevE.67.056104 Virkar, Y., & Clauset, A. (2014). Power-Law Distributions In Binned Empirical Data. Annals of Applied Statistics, 8(1), 89-119. doi: 10.1214/13-aoas710 Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 34(10), 1608-1618. doi: 10.1016/j.respol.2005.08.002 Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature, 393(6684), 440-442. doi: 10.1038/30918