Document Type : Articles


1 Payame Noor University, Tehran, Iran

2 ShahidChamran University, Ahvaz, Iran

3 Isfahan University, Isfahan, Iran


This research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, Bonacich flow betweenness) and productivity of Information science researchers. The research population includes all those researchers who have published at least one record in one of the twenty journals of Information Science which has an impact factor of 0.635 as a minimum from the years 1996 to 2010. By using social network analyses, this study examines information science researchers’ outputs during 1996-2011 in ISI Web of Science database. In general co-authorship network of these researchers was analyzed by UCINET6 software. Results showed that there is a significant correlation between Journal Impact Factor (JIF) and all centrality measures except closeness centrality at P= 0.001. Results also showed that there is a significant correlation between productivity of authors and all centrality measures scores at P≥ 0.001. Also, regression reports direct relationship of degree, closeness and flow betweenness and inverse relationship of betweenness as well as Eigen vector centrality on productivity of researchers.

  1. Acedo, F. J.; Barroso, C.; Casanueva, C.; Galan, J. L. (2006). “co-authorship in management and organizational studies: an empirical and network analysis”. Journal of Management Studies, 43:5, 957-983.
  2. Badar, K.; Hite, J. M.; Badir, Y. F. (2012). “Examining the relationship of co-authorship network centrality and gender on academic research performance: the case of chemistry researchers in Pakistan“. Scientometrics (forthcoming).
  3. Barabâsi, A. L.; Jeong; H.; Neda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T. (2002). "Evolution of the social network ofscientific collaborations". Physica A: Statistical, 311, 590–614.
  4. Betts, S. C. (2004). The network perspective in organization studies: Network organizations or network analysis?. Academy of Strategic Management Journal, 3, 1-20. Available at: Retrieved at: 4 September 2010.
  5. Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113-120.
  6. Bonacich, P. (1987). “Power and centrality: A family of measures”. The American Journal of Sociology, 92, 1170–1182.
  7. Borgatti, S. P., Everett, M. G., & Freeman, L. C. UCINet for Windows: Software for social network analysis. 2002. Harvard: Analytic Technologies.
  8. Burt, R. S. (1992). Structural holes. Cambridge. MA: Harvard University Press.
  9. Chakrabarti, D., &Faloutsos, C. (2006). Graph mining: Laws, generators, and algorithms. ACM Computing Surveys (CSUR), 38(1), 2.
  10. Emirbayer, M. (1997). Manifesto for a relational sociology. The American Journal of Sociology, 103(2), 281-317.
  11. Fatt, C. K.; Ujum. E. A.; Ratnavelu, K. (2010). "The structure of collaboration in the Journal of Finance".Scientometrics. 85:3, 849-860.
  12. Frank, O. (2002). Using centrality modeling in network surveys. Social networks, 24(4), 385-394.
  13. Freeman, L. C. (1979). Centrality in social networks conceptual clarification.Social networks, 1(3), 215-239.
  14. Gomez, C. O.; Rodriguez, A. P.; Antonia, M.; Perandones, M. A.O; Anegon, F. M.(2008). “Comparative analysis of university government enterprise co-authorship networks in three scientific domains in the region of Madrid”. Information Research, 13:3, 1-16.
  15. Gossart, C.; Özman, M. (2009). “Co-authorship networks in social sciences: The case of Turkey”. Scientometrics, 78:2, 323–345.
  16. Hanneman, R. A., Riddle, R. )2005(. Introduction to social network methods. An online text book, available at: retrieved at: 11 November 2010.
  17. Haythornthwaite, C. (1996). Social network analysis: An approach and technique for the study of information exchange. Library & Information Science Research, 18(4), 323-342.
  18. Hill, V. A. (2008). “Collaboration in an academic setting: Does the network structure matter? Center for the Computational Analysis of Social and Organizational Systems”. Available at: Retrieved at:12 may 2013.
  19. Holland, P.W., &Leinhardt, S. (1979). The advance research symposium on social networks.In P.W. Holland & S. Leinhardt (Eds.), Perspectives on social network research. New York: Academic Press.
  20. Hou, H.; Kretschmer, H.; Liu, Z. (2008). “The structure of scientific collaboration networksin Scientometrics”. Scientometrics, 75:2, 189–202.
  21. Kretschmer, H. (2004). “Author productivity and geodesic distance in bibliographic co-authorship networks,and visibility on the Web” Scientometrics, 60:3, 409–420.
  22. Krichel, T; Bakkalbasi, N. (2006).“A social network analysis of research collaboration in the economics community”.In Proceedings of International Workshop on Webometrics, Informetrics and Scientometrics& seventh COLLNET meeting, Nancy, France.
  23. Liu, L. G.; Xuan, Z. G.; Dang, Z. Y.; Guo, Q.; Wang, Z. T. (2007). “Weighted network properties of Chinese nature science basic research”.Physica A-Statistical Mechanics and Its Applications, 377:1, 302–314.
  24. Liu, X., Bollen, J., Nelson, M. L., & Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information processing & management, 41(6), 1462-1480.
  25. Lu, H.; Feng, Y. (2009). “Measure of author’s centrality in co-authorship networks based on thedistribution of collaborative relationships” Scientometrics, 81:2, 499-511.
  26. Marsden, P. V., & Campbell, K. E. (1984).Measuring tie strength. Social forces, 63(2), 482-501.
  27. Marsden, P. V. (2002). Egocentric and sociocentric measures of network centrality.Social networks, 24(4), 407-422.
  28. Mutschke, P. (2003). “Mining networks and central entities in digital libraries. A graph theoretic approach applied to co-author networks”. Advances in Intelligent Data Analysis, 2810, 155–166.
  29. Newman, M. E. J. (2001). “The structure of scientific collaboration networks”. Proceedings of the National Academy of Sciences, 98:2, 404–409.
  30. Otte, E.; Rousseau, R. (2002). “Social network analysis: A powerful strategy, also for the information sciences”. Journal of Information Science, 28:6, 443–455.
  31. Racherla, P.; Hu, C. (2010).“A social network perspective of tourism research collaborations”.Annals of Tourism Research. 37:4, 1012-1034.
  32. Said, Y. H., Wegman, E. J., Sharabati, W. K., &Rigsby, J. T. (2008).RETRACTED: Social networks of author–coauthor relationships. Computational Statistics & Data Analysis, 52(4), 2177-2184.
  33. Yoshikane, F., Nozawa, T., Tsuji, K. (2006). Comparative analysis of co-authorship networks considering authors’ roles in collaboration: differences between the theoretical and application areas. Scientometrics, 68(3), 643–655.