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The Structure of Scientific Collaboration Networks

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  • M. E. J. Newman

Abstract

We investigate the structure of scientific collaboration networks. We consider two scientists to be connected if they have authored a paper together, and construct explicit networks of such connections using data drawn from a number of databases, including MEDLINE (biomedical research), the Los Alamos e-Print Archive (physics), and NCSTRL (computer science). We show that these collaboration networks form "small worlds" in which randomly chosen pairs of scientists are typically separated by only a short path of intermediate acquaintances. We further give results for mean and distribution of numbers of collaborators of authors, demonstrate the presence of clustering in the networks, and highlight a number of apparent differences in the patterns of collaboration between the fields studied.

Suggested Citation

  • M. E. J. Newman, 2000. "The Structure of Scientific Collaboration Networks," Working Papers 00-07-037, Santa Fe Institute.
  • Handle: RePEc:wop:safiwp:00-07-037
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    1. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, vol. 61(5), pages 1047-1071, September.
    2. Young, H.P., 1999. "Diffusion in Social Networks," Papers 2, Brookings Institution - Working Papers.
    3. Page, Scott E, 1997. "On Incentives and Updating in Agent Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 10(1), pages 67-87, February.
    4. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
    5. Robert Axtell, 1999. "The Emergence of Firms in a Population of Agents," Working Papers 99-03-019, Santa Fe Institute.
    6. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, January.
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