1. A method comprising: determining, by a computer system, a plurality of subjective attributes for a first entity based on terms from a plurality of user reactions to the first entity, wherein the terms are not a user-supplied tag; determining respective relevancy scores for the plurality of subjective attributes with respect to the first entity using at least a number of occurrences of a plurality of users bookmarking the first entity; obtaining a first set of features for the first entity; and training a classifier on a set of input-output mappings, wherein the set of input-output mappings comprises an input-output mapping whose input is based on the first set of features and whose output is based on the respective relevancy scores for the plurality of subjective attributes with respect to the first entity, wherein the trained classifier is to be applied to a second set of features of a second entity to obtain respective relevancy scores for one or more subjective attributes with respect to the second entity.
5. The method of claim 1 wherein the respective relevancy score for a subjective attribute is based on a number of times that the subjective attribute appears in a set of comments pertaining to the first entity.