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The improvement of user experience through scaling bandwidth-demanding content largely depends on the exploitation of usage patterns found in OSNs. Big data analysis tasks (such as cascades characterization) accommodate large volumes of data for the improvement of user experience, eg via prefetching in the framework of a CDN infrastructure that streaming providers own. Usage patterns information can be applied in situations where traditional bandwidthintensive content scaling is infeasible: global replication demanded by traditional CDNs for the voluminous content produced becomes expensive and, moreover, user-generated content is especially difficult due to its long tail nature, with each item probably not popular enough to be replicated globally, but with the long-tail altogether getting sufficient accesses. To achieve scalability we enable proactive content delivery to key CDN nodes, by predicting future demand based on social relationships among the users and multimedia contextual information. This work presents a cloud-based architecture that could support the proposed solution for delivering social multimedia content with scalability.