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How Much Is the Whole Really More than the Sum of Its Parts? 1 ⊞ 1 = 2.5: Superlinear Productivity in Collective Group Actions

Overview of attention for article published in PLOS ONE, August 2014
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Title
How Much Is the Whole Really More than the Sum of Its Parts? 1 ⊞ 1 = 2.5: Superlinear Productivity in Collective Group Actions
Published in
PLOS ONE, August 2014
DOI 10.1371/journal.pone.0103023
Pubmed ID
Authors

Didier Sornette, Thomas Maillart, Giacomo Ghezzi

Abstract

In a variety of open source software projects, we document a superlinear growth of production intensity (R ~ c(β)) as a function of the number of active developers c, with a median value of the exponent β ≃ 4/3, with large dispersions of β from slightly less than 1 up to 3. For a typical project in this class, doubling of the group size multiplies typically the output by a factor 2(β) = 2.5, explaining the title. This superlinear law is found to hold for group sizes ranging from 5 to a few hundred developers. We propose two classes of mechanisms, interaction-based and large deviation, along with a cascade model of productive activity, which unifies them. In this common framework, superlinear productivity requires that the involved social groups function at or close to criticality, or in a "superradiance" mode, in the sense of the appearance of a cooperative process and order involving a collective mode of developers defined by the build up of correlation between the contributions of developers. In addition, we report the first empirical test of the renormalization of the exponent of the distribution of the sizes of first generation events into the renormalized exponent of the distribution of clusters resulting from the cascade of triggering over all generation in a critical branching process in the non-meanfield regime. Finally, we document a size effect in the strength and variability of the superlinear effect, with smaller groups exhibiting widely distributed superlinear exponents, some of them characterizing highly productive teams. In contrast, large groups tend to have a smaller superlinearity and less variability.

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Geographical breakdown

Country Count As %
United States 2 4%
Germany 1 2%
Australia 1 2%
Netherlands 1 2%
Estonia 1 2%
Luxembourg 1 2%
Unknown 40 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 28%
Researcher 11 23%
Student > Master 5 11%
Other 3 6%
Professor 3 6%
Other 6 13%
Unknown 6 13%
Readers by discipline Count As %
Computer Science 13 28%
Physics and Astronomy 4 9%
Engineering 4 9%
Economics, Econometrics and Finance 3 6%
Mathematics 3 6%
Other 9 19%
Unknown 11 23%