Testing for the signature of policy in online communities

Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 693)


Most successful online communities employ professionals, sometimes called “community managers”, for a variety of tasks including on boarding new participants, mediating conflict, and policing unwanted behaviour. We interpret the activity of community managers as 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. Our main hypothesis is that managed online communities would 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. We investigate the issue using empirical data on three small online communities and a computer model that simulates a widely used community management activity called on boarding. We find that the model produces in-degree distributions that systematically deviate from power law behavior for low-values of the in-degree; we then explore the implications and possible applications of the finding.


Interaction Network Degree Distribution Online Community Preferential Attachment Community Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of AlicanteAlicanteSpain
  2. 2.EdgerydersBrusselsBelgium
  3. 3.University of BordeauxBordeauxFrance
  4. 4.National Institute of Informatics & JFLI CNRS UMI 3527TokyoJapan

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