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Several existing learning object repositories provide mechanisms for users to arrange personal collections with their selection of resources or to provide reviews and ratings for other's resources, creating a kind of community dynamics. The resulting information can be used to build structural prestige models for the creators of the resources. This paper reports preliminary explorations on relational models that could be used to develop metrics of quality and prestige for learning object authors. Concretely, social network analysis tools are used to analyze the overall community structure of a dataset obtained from the MERLOT repository. Networks extracted from the indirect reference between users through references in personal collections and reviews are examined with regards to the position of relevant community members.