1. A method comprising, by one or more computing systems: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes corresponding to a plurality of content objects associated with an online social network; receiving an input from a user, wherein the input comprises free-form text; determining, through application of natural-language processing of the free-form text, one or more objects associated with the input, each object corresponding to one of the plurality of nodes in the social graph, wherein each of the one or more objects comprises a noun detected in the free-form text; determining, through application of natural-language processing of the free-form text, one or more affinity declarations associated with the one or more objects; determining, from the one or more objects, a first concept and a second concept, the first concept corresponding to a first node in the social graph, the second concept corresponding to a second node in the social graph, wherein the first concept is a specific instance of the second concept; determining a first affinity coefficient between the user and the first concept based on the one or more affinity declarations; inferring a second affinity coefficient between the user and the second concept, wherein the inference is based on: the first affinity coefficient; and social networking information of the user; storing the first affinity coefficient in a data store in association with the user and the first concept; dynamically adjusting the inferred second affinity coefficient based on social-networking information of the user, wherein the social-networking information reinforces or reduces the inferred second affinity coefficient; and upon determining that the inferred second affinity coefficient for a threshold number of users exceeds a predetermined number, creating a hub page associated with the first concept for display on an online social network.