Español
Valencià
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 a variety of 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 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 characterized by degree distributions that deviate from the power law form; such deviation constitutes the signature of successful community management. If true, this hypothesis would give us with a simple test for the effectiveness of community management practices. Our secondary hypothesis is that said deviation happens in a predictable way, once community management practices are accounted for. We proceed as follows. First, we examine empirical data on three online communities, two of which are known to be managed with the same goals and practices, whereas the third is known not to be. We run statistical tests of the null hypothesis that their degree distribution was generated by a power function; the test strongly rejects the null for the two managed communities, and does not reject it for the unmanaged one. This result is in agreement with our main hypothesis. Next, we investigate the impact of community management practices on the interaction network of online communities by simulation techniques. We build a model of interaction in an online community on which community management practices are enacted. We explore its evolution under the assumptions of growth, preferential attachment and presence of some of the most widespread online community management practices. We then discuss the effect of the model’s specification on the degree distribution of the simulated interaction network.