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      Cues to gender and racial identity reduce creativity in diverse social networks

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          Abstract

          The characteristics of social partners have long been hypothesized as influential in guiding group interactions. Understanding how demographic cues impact networks of creative collaborators is critical for elevating creative performances therein. We conducted a randomized experiment to investigate how the knowledge of peers’ gender and racial identities distorts people’s connection patterns and the resulting creative outcomes in a dynamic social network. Consistent with prior work, we found that creative inspiration links are primarily formed with top idea-generators. However, when gender and racial identities are known, not only is there (1) an increase of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$82.03\%$$\end{document} in the odds of same-gender connections to persist (but not for same-race connections), but (2) the semantic similarity of idea-sets stimulated by these connections also increase significantly compared to demography-agnostic networks, negatively impacting the outcomes of divergent creativity. We found that ideas tend to be significantly more homogeneous within demographic groups than between, taking away diversity-bonuses from similarity-based links and partly explaining the results. These insights can inform intelligent interventions to enhance network-wide creative performances.

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          Most cited references53

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          Birds of a Feather: Homophily in Social Networks

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            An introduction to exponential random graph (p*) models for social networks

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              Structural Holes and Good Ideas

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                Author and article information

                Contributors
                mehoque@cs.rochester.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                13 May 2021
                13 May 2021
                2021
                : 11
                : 10261
                Affiliations
                [1 ]GRID grid.16416.34, ISNI 0000 0004 1936 9174, Department of Electrical and Computer Engineering, , University of Rochester, ; Rochester, NY USA
                [2 ]GRID grid.47100.32, ISNI 0000000419368710, Haskins Laboratories and Department of Psychology, , Yale University, ; New Haven, CT USA
                [3 ]GRID grid.16416.34, ISNI 0000 0004 1936 9174, Department of Physics and Astronomy, , University of Rochester, ; Rochester, NY USA
                [4 ]GRID grid.16416.34, ISNI 0000 0004 1936 9174, Department of Computer Science, , University of Rochester, ; Rochester, NY USA
                Article
                89498
                10.1038/s41598-021-89498-5
                8119436
                33986339
                45f2c034-289c-43e4-b74a-ba44d7640a44
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 February 2021
                : 21 April 2021
                Funding
                Funded by: National Science Foundation
                Award ID: IIS1750380
                Award ID: IIS1750380
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: HD-037082
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000183, Army Research Office;
                Award ID: W911NF-18-1-0421
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                human behaviour,computational science,computer science
                Uncategorized
                human behaviour, computational science, computer science

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