Advertisement

The Structure of Organization: The Coauthorship Network Case

Conference paper
  • 998 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 661)

Abstract

A balanced social structure within an organization is often considered as one of the major factors of company success. Thus the analysis of organizational networks is an important direction in network and organizational studies. In this paper we explore the mechanisms of collaboration using information about scientific paper coauthorships. We reveal the collaboration mechanisms within research departments of top Russian oil companies, Gazpromneft, Bashneft, Lukoil, and Tatneft. We examine the role of management in professional community formation.

Keywords

Coauthorship graph Real structure of an organization Professional network Professional community Research management 

References

  1. 1.
    Newman, M.E.: The structure of scientific collaboration networks. Proc. Nat. Acad. Sci. 98(2), 404–409 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Ushakov, K.: Diagnostics of an educational institution real structure. Educ. Stud. 4, 247–260 (2013)Google Scholar
  3. 3.
    Agneessens, F., Wittek, R.: Where do intra-organizational advice relations come from? The role of informal status and social capital in social exchange. Soc. Netw. 34(3), 333–345 (2012)CrossRefGoogle Scholar
  4. 4.
    Ellwardt, L., Steglich, C., Wittek, R.: The co-evolution of gossip and friendship in workplace social networks. Soc. Netw. 34(4), 623–633 (2012)CrossRefGoogle Scholar
  5. 5.
    Krackhardt, D.: The ties that torture: Simmelian tie analysis in organizations. Res. Sociol. Organ. 16(1), 183–210 (1999)Google Scholar
  6. 6.
    Krackhardt, D.: Assessing the political landscape: structure, cognition, and power in organizations. Adm. sci. Q. 35, 342–369 (1990)CrossRefGoogle Scholar
  7. 7.
    Krackhardt, D., Hanson, J.R.: Informal networks. Harvard Bus. Rev. 71(4), 104–111 (1993)Google Scholar
  8. 8.
    Krasnov, F., Vlasova, E., Yavorskiy, R.: Connectivity analysis of computer science centers based on scientific publications datafor major russian cities. Procedia Comput. Sci. 31, 892–899 (2014)CrossRefGoogle Scholar
  9. 9.
    Krasnov, F., Yavorskiy, R.: Measurement of maturity level of a professional community. Bus. Inf. 1(23), 64–67 (2013)Google Scholar
  10. 10.
    Krasnov, F., Yavorskiy, R.E., Vlasova, E.: Indicators of connectivity for urban scientific communities in Russian cities. In: Ignatov, D.I., Khachay, M.Y., Panchenko, A., Konstantinova, N., Yavorskiy, R.E. (eds.) AIST 2014. CCIS, vol. 436, pp. 111–120. Springer, Heidelberg (2014). doi: 10.1007/978-3-319-12580-0_11 Google Scholar
  11. 11.
    Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications, vol. 8. Cambridge University Press, Cambridge (1994)CrossRefzbMATHGoogle Scholar
  12. 12.
    Prell, C.: Social Network Analysis: History, Theory and Methodology. Sage, London (2012)Google Scholar
  13. 13.
    Hou, H., Kretschmer, H., Liu, Z.: The structure of scientific collaboration networks in scientometrics. Scientometrics 75(2), 189–202 (2008)CrossRefGoogle Scholar
  14. 14.
    Barabási, A.L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., Vicsek, T.: Evolution of the social network of scientific collaborations. Phys. A Stat. Mech. Appl. 311(3), 590–614 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Rodriguez, M.A., Pepe, A.: On the relationship between the structural and socioacademic communities of a coauthorship network. J. Informetrics 2(3), 195–201 (2008)CrossRefGoogle Scholar
  16. 16.
    Ding, Y.: Scientific collaboration and endorsement: network analysis of coauthorship and citation networks. J. Informetrics 5(1), 187–203 (2011)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Acedo, F.J., Barroso, C., Casanueva, C., Galán, J.L.: Co-authorship in management and organizational studies: an empirical and network analysis. J. Manage. Stud. 43(5), 957–983 (2006)CrossRefGoogle Scholar
  18. 18.
    R Core Team: R: a language and environment for statistical computing. R foundation for statistical computing 2013, Vienna, Austria (2014)Google Scholar
  19. 19.
    Anderson, B.S., Butts, C., Carley, K.: The interaction of size and density with graph-level indices. Soc. Netw. 21(3), 239–267 (1999)CrossRefGoogle Scholar
  20. 20.
    Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Gazpromneft NTCSt. PetersburgRussia
  2. 2.Center for Institutional StudiesHigher School of EconomicsMoscowRussia
  3. 3.Department of Data Analysis and Artificial Intelligence, Faculty of Computer ScienceHigher School of EconomicsMoscowRussia

Personalised recommendations