Collective Credit Allocation in Science. Shen, H. W. & Barabasi, A. L. Proceedings of the National Academy of Sciences of the United States of America, 111(34):12325–12330, August, 2014. doi abstract bibtex [Significance] The increasing dominance of multiauthor papers is straining the credit system of science: although for single-author papers, the credit is obvious and undivided, for multiauthor papers, credit assignment varies from discipline to discipline. Consequently, each research field runs its own informal credit allocation system, which is hard to decode for outsiders. Here we develop a discipline-independent algorithm to decipher the collective credit allocation process within science, capturing each coauthor's perceived contribution to a publication. The proposed method provides scientists and policy-makers an effective tool to quantify and compare the scientific contribution of each researcher without requiring familiarity with the credit allocation system of the specific discipline. [Abstract] 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.
@article{shenCollectiveCreditAllocation2014,
title = {Collective Credit Allocation in Science.},
author = {Shen, H. W. and Barabasi, A. L.},
year = {2014},
month = aug,
volume = {111},
pages = {12325--12330},
issn = {1091-6490},
doi = {10.1073/pnas.1401992111},
abstract = {[Significance]
The increasing dominance of multiauthor papers is straining the credit system of science: although for single-author papers, the credit is obvious and undivided, for multiauthor papers, credit assignment varies from discipline to discipline. Consequently, each research field runs its own informal credit allocation system, which is hard to decode for outsiders. Here we develop a discipline-independent algorithm to decipher the collective credit allocation process within science, capturing each coauthor's perceived contribution to a publication. The proposed method provides scientists and policy-makers an effective tool to quantify and compare the scientific contribution of each researcher without requiring familiarity with the credit allocation system of the specific discipline. [Abstract]
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.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13322272,~to-add-doi-URL,authorship,citation-metrics,cooperation,research-metrics,science-ethics},
lccn = {INRMM-MiD:c-13322272},
number = {34}
}
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