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In many large-scale content sharing applications, participants or nodes are connected with each other based on their content or interests, thus forming clusters. In this paper, we model the formation of such clustered overlays as a strategic game, where nodes determine their cluster membership with the goal of improving the recall of their queries. We study the evolution of such overlays both theoretically and experimentally in terms of stability, optimality, load balance, and the required overhead. We show that, in general, decisions made independently by each node using only local information lead to overall cost-effective cluster configurations that are also dynamically adaptable to system updates such as churn and query or content changes.