Online community management as social network design: testing for the signature of management activities in online communities
RENOUST, Benjamin
National Institute of Informatics [NII]
Japanese French Laboratory for Informatics [JFLI]
National Institute of Informatics [NII]
Japanese French Laboratory for Informatics [JFLI]
RENOUST, Benjamin
National Institute of Informatics [NII]
Japanese French Laboratory for Informatics [JFLI]
< Réduire
National Institute of Informatics [NII]
Japanese French Laboratory for Informatics [JFLI]
Langue
EN
Article de revue
Ce document a été publié dans
Applied Network Science. 2017-08-30, vol. 2, n° 1
Résumé en anglais
Online 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 ...Lire la suite >
Online 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.< Réduire
Mots clés en anglais
Collective intelligence
Online communities
Network structure
Lien vers les données de la recherche
Projet Européen
ERC Horizon H2020
Unités de recherche