Social content such as social network posts, tweets, news articles and more generally web page fragments is often structured. Such social content is also frequently enriched with annotations, most of which carry semantics, either by collaborative effort or from automatic tools. Searching for relevant informa-tion in this context is both a basic feature for the users and a challenging task. We present a data model and a preliminary approach for answering queries over such structured, social and semantic-rich content, taking into account all dimensions of the data in order to return the most meaningful results.