The scaling relationship between citation‐based performance and coauthorship patterns in natural sciences
- 21 December 2016
- journal article
- research article
- Published by Wiley in Journal of the Association for Information Science and Technology
- Vol. 68 (5) , 1257-1265
Abstract
The aim of this paper is to extend our knowledge about the power‐law relationship between citation‐based performance and coauthorship patterns in papers in the natural sciences. We analyzed 829,924 articles that received 16,490,346 citations. The number of articles published through coauthorship accounts for 89%. The citation‐based performance and coauthorship patterns exhibit a power‐law correlation with a scaling exponent of 1.20 ± 0.07. Citations to a subfield's research articles tended to increase 2.1.20 or 2.30 times each time it doubled the number of coauthored papers. The scaling exponent for the power‐law relationship for single‐authored papers was 0.85 ± 0.11. The citations to a subfield's single‐authored research articles increased 2.0.85 or 1.89 times each time the research area doubled the number of single‐authored papers. The Matthew Effect is stronger for coauthored papers than for single‐authored. In fact, with a scaling exponent <1.0 the impact of single‐authored papers exhibits a cumulative disadvantage or inverse Matthew Effect.Keywords
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This publication has 40 references indexed in Scilit:
- Universities Scale Like CitiesPLOS ONE, 2013
- A new methodology for constructing a publication‐level classification system of scienceJournal of the American Society for Information Science and Technology, 2012
- Modes of collaboration in modern science: Beyond power laws and preferential attachmentJournal of the American Society for Information Science and Technology, 2010
- Scaling rules in the science system: Influence of field‐specific citation characteristics on the impact of research groupsJournal of the American Society for Information Science and Technology, 2008
- Bibliometric statistical properties of the 100 largest European research universities: Prevalent scaling rules in the science systemJournal of the American Society for Information Science and Technology, 2007
- Preferential attachment and growth dynamics in complex systemsPhysical Review E, 2006
- Web indicators for complex innovation systemsResearch Evaluation, 2006
- Power laws, Pareto distributions and Zipf's lawContemporary Physics, 2005
- Statistical mechanics of complex networksReviews of Modern Physics, 2002
- Scale-independent indicators and research evaluationScience and Public Policy, 2000