Abstract
Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Acedo F.J., Barroso C., Casanueva C., Galán J.L.: Co-authorship in management and organizational studies: an empirical and network analysis. J. Manag. Stud. 43, 957–983 (2006)
Albert R., Barabási A.-L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)
Babchuk N., Keith B., Peters G.: Collaboration in sociology and other scientific disciplines: a comparative trend analysis of scholarship in the social. Phys. Math. Sci. Am. Sociol. 30, 5–21 (1999)
Bakkalbasi N., Krichel T.: Patterns of research collaboration in a digital library for Economics (2006). Proc. Am. Soc. Inform. Sci. Technol. 43, 1–15 (2006)
Barabási A.-L., Albert R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Barabási A.-L., Jeong H., Neda Z., Ravasz E., Schubert A., Vicsek T.: Evolution of the social network of scientific collaborations. Phys. A 311(3-4), 590–614 (2002)
Bonacich P.: Power and centrality: a family of measures. Am. J. Sociol. 92, 1170–1182 (1987)
Brandes U.: On variants of shortest-path betweenness centrality and their generic computation. Soc. Netw. 30, 136–145 (2008)
Butts, C.T.: sna: Tools for Social Network Analysis. R package version 2.1. (2010)
Doreian P., Woodard K.L.: Fixed list versus snowball selection of social networks. Soc. Sci. Res. 21, 216–233 (1992)
Endersby J.W.: Collaborative research in the social sciences: multiple authorship and paper credit. Soc. Sci. Quart. 77, 375–392 (1996)
Ferligoj A., Kronegger L.: Clustering of attribute and/or relational data. Metodoloski zvezki 6, 135–153 (2009)
Freeman L.C.: Centrality in social networks I: conceptual clarification. Soc. Netw. 1, 215–239 (1979)
Gibbons M., Limoges C., Nowotny H., Schwartzman S., Scott P., Trow M.: The New Production of Knowledge. Sage, London (1994)
Glanzel W., Schubert A.: Analyzing scientific networks through co-authorship. In: Moed, H., Glanzel, W., Schmoch , U. (eds) Handbook of Quantitative Science and Technology Research, pp. 257–276. Springer, Netherlands (2005)
Gossart C., Ozman M.: Co-authorship networks in social sciences: the case of Turkey. Scientometrics 78, 323–345 (2009)
Goyal S., Vander Leij M.J., Moraga-González J.L.: Economics: an emerging small world. J. Political Econ. 114, 403–412 (2006)
Hargens L.L.: Patterns of Scientific Research: A Comparative Analysis of Research in three Scientific Fields. American Sociological Association, Washington, DC (1975)
Hicks D.: The difficulty of achieving full coverage of international social science literature and the bibliometric consequences. Scientometrics 44, 193–215 (1999)
Hudson J.: Trends in multi-authored papers in economics. J. Econ. Perspect. 10, 153–158 (1996)
Kaiser M.: Mean clustering coefficients—the role of isolated nodes and leafs on clustering measures for small-world networks. New J. Phys. 10(8), 083042 (2008)
Katz J.S., Martin B.R.: What is research collaboration?. Res. Policy 26, 1–18 (1997)
Laband D.N., Tollison R.D.: Intellectual Collaboration. J. Political Econ. 108, 632–662 (2000)
Laumann E.O., Marsden P., Prensky D.: The boundary specification problem in network analysis. In: Freeman, L.C., White, D.R., Kimball Romney, A. (eds) Research Methods in Social Network Analysis, George Mason University Press, Fairfax, VA (1989)
Lotka A.J.: The frequency distribution of scientific productivity. J. Wash. Acad. Sci. 16, 317–323 (1926)
Marsden P.V.: Recent developments in network measurement. In: Carrington, P., Scott, J., Wasserman, S. (eds) Models and Methods in Social Network Analysis, Cambridge University Press, New York (2005)
Melin G., Persson O.: Studying research collaboration using co-authorships. Scientometrics 36, 363–377 (1996)
Moody J.: The structure of a social science: disciplinary cohesion from 1963 to 1999. Am. Sociol. Rev. 69, 213–238 (2004)
Newman M.E.J.: Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Phys. Rev. E 64, 0161321–0161327 (2001)
Newman M.E.J.: Coauthorship networks and patterns of scientific collaboration. Proc. Natl. Acad. Sci. 101, 5200–5205 (2004)
Nicholls P.T.: Empirical validation of Lotka’s law. Inf. Process. Manag. 22, 417–419 (1986)
Said Y., Wegman E., Sharabati : Author-coauthor social networks and emerging scientific subfield. In: Palumbo, F., Lauro, N.C., Greenacre, M.J. (eds) Data Analysis and Classification, Springer, Berlin (2010)
Wasserman S., Faust K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)
Watts D., Strogatz S.: Collective dynamics of small world networks. Nature 393, 440–442 (1998)
Yoshikane F., Kageura K.: Comparative analysis of coauthorship networks of different domains: The growth and change of networks. Scientometrics 60, 433–444 (2004)
Yousefi-Nooraie, R., Akbari-Kamrani, M., Hanneman, R., Etemadi, A.: Association between co-authorship network and scientific productivity and impact indicators in academic medical research centers: a case study in Iran. Health Res. Policy Syst. 6 (2008)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
De Stefano, D., Giordano, G. & Vitale, M.P. Issues in the analysis of co-authorship networks. Qual Quant 45, 1091–1107 (2011). https://doi.org/10.1007/s11135-011-9493-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11135-011-9493-2