1. A computer system for using an emergent self-organization characteristic in a natural language for establishing a collaborative content relevance between users and items in a context space, the computer system comprising: at least one processing unit and at least one computer-readable media for storing instructions for implementation by the at least one processing unit and data used by the at least one processing unit in implementing instructions, wherein the at least one processing unit includes: means for identifying a plurality of items in the context space with unique item identifiers, one of the plurality of items capable of being independently annotated in the context space by one or more of a plurality of users operating independently of one another without knowledge of each other's activities or existence, the annotating being done in the context space with unique user identifiers using an annotation of at least one keyword from the natural language during an annotation event, the annotation including an association between the at least one keyword, one of the unique item identifiers associated with the one of the plurality of items being independently annotated, and one of the unique user identifiers associated with the independently annotating one of the plurality of users; means for copying each of the annotations generated during ones of the annotation event to the at least one computer-readable media for storage therein, the stored annotations containing the ones of the unique user identifier of the independently annotating ones of the plurality of users, the ones of the unique item identifier of the ones of the items being independently annotated, and the at least one keyword, ones of the plurality of users capable of using a different keyword to annotate the same one of the plurality of items; means for aggregating the stored annotations based on a correlation between users, items and keywords to form the collaborative content relevance between the plurality of items and the plurality of users; and means for associating, using the collaborative content relevance, one of: ones of the plurality of users with other ones of the plurality of users; and ones of the plurality of items with ones of the plurality of users such that the ones of the plurality of users are capable of discovering the other ones of the plurality of users, and the ones of the plurality of items are capable of discovering the ones of the plurality of users, based on the associated collaborative content relevance.