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Collective credit allocation in science
by
Shen, Hua-Wei
, Barabási, Albert-László
in
Algorithms
/ Allocations
/ Authorship
/ Authorship attribution
/ Average propensity to save
/ business enterprises
/ Collaboration
/ Comparative analysis
/ Cooperative Behavior
/ credit
/ Datasets
/ funding
/ hiring
/ Humans
/ Multidisciplinary research
/ Nobel Prize
/ Nobel Prizes
/ Particle physics
/ Physical Sciences
/ Physics
/ Publishing
/ Research methods
/ Research papers
/ Research Personnel
/ researchers
2014
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Collective credit allocation in science
by
Shen, Hua-Wei
, Barabási, Albert-László
in
Algorithms
/ Allocations
/ Authorship
/ Authorship attribution
/ Average propensity to save
/ business enterprises
/ Collaboration
/ Comparative analysis
/ Cooperative Behavior
/ credit
/ Datasets
/ funding
/ hiring
/ Humans
/ Multidisciplinary research
/ Nobel Prize
/ Nobel Prizes
/ Particle physics
/ Physical Sciences
/ Physics
/ Publishing
/ Research methods
/ Research papers
/ Research Personnel
/ researchers
2014
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Do you wish to request the book?
Collective credit allocation in science
by
Shen, Hua-Wei
, Barabási, Albert-László
in
Algorithms
/ Allocations
/ Authorship
/ Authorship attribution
/ Average propensity to save
/ business enterprises
/ Collaboration
/ Comparative analysis
/ Cooperative Behavior
/ credit
/ Datasets
/ funding
/ hiring
/ Humans
/ Multidisciplinary research
/ Nobel Prize
/ Nobel Prizes
/ Particle physics
/ Physical Sciences
/ Physics
/ Publishing
/ Research methods
/ Research papers
/ Research Personnel
/ researchers
2014
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Journal Article
Collective credit allocation in science
2014
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Overview
Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, because the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors’ contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions.
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