Online community management as social network design: testing for the signature of management activities in online communities

• Published in: Applied network science Vol. 2; no. 1; p. 30
• Main Authors: Cottica, Alberto, Melançon, Guy, Renoust, Benjamin
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2017; Springer Nature B.V; Springer; SpringerOpen
• Subjects: Collective intelligence; Complexity; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computer simulation; Deviation; Hypotheses; Management; Network design; Network structure; Online communities; Orientations; Power law; Simulation and Modeling; Social networks; Special Issue of the 5th International Workshop on Complex Networks and Their Applications; Collective intelligence; Network structure; Online communities
• ISSN: 2364-8228; 2364-8228
• DOI: 10.1007/s41109-017-0049-9

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.