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dc.rights.licenseopenen_US
hal.structure.identifierUniversidad de Alicante
dc.contributor.authorCOTTICA, Alberto
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorMELANCON, Guy
IDREF: 035315059
hal.structure.identifierNational Institute of Informatics [NII]
hal.structure.identifierJapanese French Laboratory for Informatics [JFLI]
dc.contributor.authorRENOUST, Benjamin
dc.date.accessioned2020-02-12T09:36:54Z
dc.date.available2020-02-12T09:36:54Z
dc.date.created2017-06-21
dc.date.issued2017-08-30
dc.identifier.issn2364-8228en_US
dc.identifier.otherhttps://github.com/albertocottica/communities-network-design/en_US
dc.identifier.urioai:crossref.org:10.1007/s41109-017-0049-9
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/27
dc.description.abstractEnOnline communities are used across several fields of human activities, as environments for large-scale collaboration. Most successful ones employ professionals, sometimes called “community managers” or “moderators”, for tasks including onboarding new participants, mediating conflict, and policing unwanted behaviour. Network scientists routinely model interaction across participants in online communities as social networks. We interpret the activity of community managers as (social) network design: they take action oriented at shaping the network of interactions in a way conducive to their community’s goals. It follows that, if such action is successful, we should be able to detect its signature in the network itself. Growing networks where links are allocated by a preferential attachment mechanism are known to converge to networks displaying a power law degree distribution. Growth and preferential attachment are both reasonable first-approximation assumptions to describe interaction networks in online communities. Our main hypothesis is that managed online communities are characterised by in-degree distributions that deviate from the power law form; such deviation constitutes the signature of successful community management. Our secondary hypothesis is that said deviation happens in a predictable way, once community management practices are accounted for. If true, these hypotheses would give us a simple test for the effectiveness of community management practices. We investigate the issue using (1) empirical data on three small online communities and (2) a computer model that simulates a widely used community management activity called onboarding. We find that onboarding produces in-degree distributions that systematically deviate from power law behaviour for low-values of the in-degree; we then explore the implications and possible applications of the finding.
dc.language.isoENen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.sourcecrossref
dc.subject.enCollective intelligence
dc.subject.enOnline communities
dc.subject.enNetwork structure
dc.title.enOnline community management as social network design: testing for the signature of management activities in online communities
dc.typeArticle de revueen_US
dc.identifier.doi10.1007/s41109-017-0049-9en_US
dc.subject.halInformatique [cs]en_US
dc.description.sponsorshipEuropeERC Horizon H2020en_US
bordeaux.journalApplied Network Scienceen_US
bordeaux.volume2en_US
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800en_US
bordeaux.issue1en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcedissemin
hal.identifierhal-02475587
hal.version1
hal.date.transferred2020-02-12T09:37:01Z
hal.exporttrue
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