The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Understanding Patterns of International Scientific Collaboration
Abstract
International scientific collaboration has increased both in volume and importance. In this article, the authors study the interpretation of macro-level data on international co authorship collaboration. They address such questions as how one might explain country- to-country differences in the rates of international coauthorship, networks of interna tional scientific collaboration among countries, and patterns of international collaboration in scientific fields. Attention is drawn to cognitive, social, historical, geopolitical, and economic factors as potential determinants of the observed patterns. They present a methodology that gives one a measure, independent of size, of countries'propensities to collaborate internationally.
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Cites
Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis
Kruskal, J. B. (1964) · Psychometrika · doi:10.1007/bf02289565 · Cited by 7,317
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Latour, B. (1987) · Cited by 4,106
Little Science, Big Science...and Beyond
Price, D. J. D. S. (1986) · CERN Document Server (European Organization for Nuclear Research) · Cited by 863
Studies in scientific collaboration: Part I. The professional origins of scientific co-authorship
Beaver, D. D., & Rosen, R. (1978) · Scientometrics · doi:10.1007/bf02016840 · Cited by 509
de Beaver, D. B., & Rosen, R. (1979) · Scientometrics · doi:10.1007/bf02016966 · Cited by 390
International Research Collaboration
Davidson Frame, J., & Carpenter, M. P. (1979) · Social Studies of Science · doi:10.1177/030631277900900405 · Cited by 326
Quantitative Measures of Communication in Science: A Critical Review
Edge, D. (1979) · History of Science · doi:10.1177/007327537901700202 · Cited by 283
International collaboration in the sciences 1981–1985
Schubert, A., & Braun, T. (1990) · Scientometrics · doi:10.1007/bf02130461 · Cited by 181
Coauthorship, Social Structure and Influence Within Specialties
Stokes, T., & Hartley, J. A. (1989) · Social Studies of Science · doi:10.1177/030631289019001003 · Cited by 111
Cited by
How to normalize cooccurrence data? An analysis of some well‐known similarity measures
Eck, N. J. V., & Waltman, L. (2009) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21075 · Cited by 966
Analysing Scientific Networks Through Co-Authorship
Glänzel, W., & Schubert, A. (2006) · Handbook of Quantitative Science and Technology Research · doi:10.1007/1-4020-2755-9_12 · Cited by 818
The geographical and institutional proximity of research collaboration
Ponds, R., Van Oort, F., & Frenken, K. (2007) · Papers in Regional Science · doi:10.1111/j.1435-5957.2007.00126.x · Cited by 645
Team size matters: Collaboration and scientific impact since 1900
Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23266 · Cited by 484
Springer Handbook of Science and Technology Indicators
(2019) · Springer Handbooks · doi:10.1007/978-3-030-02511-3 · Cited by 300
Metadata
- Authors
- Luukkonen, T., Persson, O., & Sivertsen, G.
- Venue
- Science, Technology, & Human Values
- Publisher
- SAGE Publications
- Published
- 1992-01
- Volume
- 17
- Issue
- 1
- Pages
- 101-126
- ISSN
- 0162-2439 (ISSN-L)
- 1552-8251
- OpenAlex
- W2050731935
- Cited by
- 573
- References
- 11
- FWCI
- 8.62
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
