In search of diverse and connected teams: A computational approach to assemble diverse teams based on members’ social networks

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dc.article.numbere0276061
dc.catalogadorvzp
dc.contributor.authorGómez Zara, Diego Alonso
dc.contributor.authorDas, Archan
dc.contributor.authorPawlow, Bradley
dc.contributor.authorContractor, Noshir
dc.date.accessioned2024-03-14T18:27:33Z
dc.date.available2024-03-14T18:27:33Z
dc.date.issued2022
dc.description.abstractPrevious research shows that teams with diverse backgrounds and skills can outperform homogeneous teams. However, people often prefer to work with others who are similar and familiar to them and fail to assemble teams with high diversity levels. We study the team formation problem by considering a pool of individuals with different skills and characteristics, and a social network that captures the familiarity among these individuals. The goal is to assign all individuals to diverse teams based on their social connections, thereby allowing them to preserve a level of familiarity. We formulate this team formation problem as a multiobjective optimization problem to split members into well-connected and diverse teams within a social network. We implement this problem employing the Non-dominated Sorting Genetic Algorithm II (NSGA-II), which finds team combinations with high familiarity and diversity levels in O(n2) time. We tested this algorithm on three empirically collected team formation datasets and against three benchmark algorithms. The experimental results confirm that the proposed algorithm successfully formed teams that have both diversity in member attributes and previous connections between members. We discuss the benefits of using computational approaches to augment team formation and composition.
dc.description.funder2020 Microsoft Research
dc.description.funderNational Science Foundation
dc.description.funderNational Institute of Health
dc.description.funderDirectorate for Social, Behavioral and Economic Sciences
dc.description.funderNational Aeronautics and Space Administration
dc.description.funderMicrosoft Research
dc.fechaingreso.objetodigital2024-11-06
dc.fuente.origenORCID
dc.identifier.doi10.1371/journal.pone.0276061
dc.identifier.eissn19326203
dc.identifier.pubmedid36350821
dc.identifier.scopusidSCOPUS_ID:85141526784
dc.identifier.urihttps://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0276061&type=printable
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0276061
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/84425
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0276061
dc.identifier.wosidWOS:000924711500019
dc.information.autorucEscuela de Ingeniería; Gomez Zara Diego Alonso; 0000-0002-4609-6293; 162316
dc.issue.numero9
dc.language.isoen
dc.nota.accesoContenido completo
dc.publisherPublic Library of Science
dc.relation.ispartofPLoS ONE
dc.revistaPLoS ONE
dc.rightsacceso abierto
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc000
dc.subject.deweyCiencias de la computación
dc.subject.ods11 Sustainable cities and communities
dc.subject.ods03 Good health and well-being
dc.subject.odspa11 Ciudades y comunidades sostenibles
dc.subject.odspa03 Salud y bienestar
dc.titleIn search of diverse and connected teams: A computational approach to assemble diverse teams based on members’ social networks
dc.typeartículo
dc.volumen17
sipa.codpersvinculados162316
sipa.trazabilidadSCOPUS;02-03-2023
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