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Universities Scale Like Cities

Overview of attention for article published in PLOS ONE, March 2013
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Title
Universities Scale Like Cities
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0059384
Pubmed ID
Authors

Anthony F. J. van Raan

Abstract

Recent studies of urban scaling show that important socioeconomic city characteristics such as wealth and innovation capacity exhibit a nonlinear, particularly a power law scaling with population size. These nonlinear effects are common to all cities, with similar power law exponents. These findings mean that the larger the city, the more disproportionally they are places of wealth and innovation. Local properties of cities cause a deviation from the expected behavior as predicted by the power law scaling. In this paper we demonstrate that universities show a similar behavior as cities in the distribution of the 'gross university income' in terms of total number of citations over 'size' in terms of total number of publications. Moreover, the power law exponents for university scaling are comparable to those for urban scaling. We find that deviations from the expected behavior can indeed be explained by specific local properties of universities, particularly the field-specific composition of a university, and its quality in terms of field-normalized citation impact. By studying both the set of the 500 largest universities worldwide and a specific subset of these 500 universities--the top-100 European universities--we are also able to distinguish between properties of universities with as well as without selection of one specific local property, the quality of a university in terms of its average field-normalized citation impact. It also reveals an interesting observation concerning the working of a crucial property in networked systems, preferential attachment.

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Geographical breakdown

Country Count As %
Netherlands 2 3%
United States 2 3%
South Africa 1 1%
United Kingdom 1 1%
Mexico 1 1%
Brazil 1 1%
Japan 1 1%
Spain 1 1%
Venezuela, Bolivarian Republic of 1 1%
Other 1 1%
Unknown 57 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 17%
Professor 10 14%
Other 8 12%
Student > Ph. D. Student 8 12%
Student > Master 5 7%
Other 14 20%
Unknown 12 17%
Readers by discipline Count As %
Social Sciences 14 20%
Environmental Science 6 9%
Computer Science 6 9%
Earth and Planetary Sciences 4 6%
Agricultural and Biological Sciences 4 6%
Other 20 29%
Unknown 15 22%