1. A computer-implemented method for ranking information content, said method comprising: receiving a search request specifying one or more search criteria from a first individual; identifying a preliminary document list of multiple documents corresponding to said search request by searching a corpus using said search criteria; identifying one or more content elements in the multiple documents in said preliminary document list; assigning a value to at least one document in said preliminary document list based on a score for at least one of the one or more content elements in said at least one document, wherein said score is based on (i) one or more metrics of one or more social networks and (ii) a performance measure of one or more related individuals that accessed one or more of said multiple documents having at least one of the one or more identified content elements, and wherein said score is further based on a regression model between said performance measure and one or more of said content elements, wherein: at least one of said one or more metrics is a topological feature of a topic sub-network comprising two or more individuals based on a weighted value derived from communication between two or more individuals within said one or more social networks, wherein said value is weighted based on an amount of communication pertaining to a topic between the two or more individuals, at least one of said one or more metrics is a network constraint metric measuring a degree to which an individual has diverse contacts in a network with respect to other contacts in the network, wherein an increase in the diverse contacts provides an increase in information sources to improve productivity of the individual, at least one of said one or more metrics is a graph entropy metric measuring the concentration of one or more given individuals clustered across each partition of multiple partitions associated with the topic in the one or more social networks, and said performance measure comprises revenue generated by each related individual of said one or more related individuals; and providing search results based on said value assigned to the at least one document in said preliminary document list, wherein one or more steps of said method are performed by one or more hardware devices.
1. A computer-implemented method for ranking information content, said method comprising: receiving a search request specifying one or more search criteria from a first individual; identifying a preliminary document list of multiple documents corresponding to said search request by searching a corpus using said search criteria; identifying one or more content elements in the multiple documents in said preliminary document list; assigning a value to at least one document in said preliminary document list based on a score for at least one of the one or more content elements in said at least one document, wherein said score is based on (i) one or more metrics of one or more social networks and (ii) a performance measure of one or more related individuals that accessed one or more of said multiple documents having at least one of the one or more identified content elements, and wherein said score is further based on a regression model between said performance measure and one or more of said content elements, wherein: at least one of said one or more metrics is a topological feature of a topic sub-network comprising two or more individuals based on a weighted value derived from communication between two or more individuals within said one or more social networks, wherein said value is weighted based on an amount of communication pertaining to a topic between the two or more individuals, at least one of said one or more metrics is a network constraint metric measuring a degree to which an individual has diverse contacts in a network with respect to other contacts in the network, wherein an increase in the diverse contacts provides an increase in information sources to improve productivity of the individual, at least one of said one or more metrics is a graph entropy metric measuring the concentration of one or more given individuals clustered across each partition of multiple partitions associated with the topic in the one or more social networks, and said performance measure comprises revenue generated by each related individual of said one or more related individuals; and providing search results based on said value assigned to the at least one document in said preliminary document list, wherein one or more steps of said method are performed by one or more hardware devices. 7. The method of claim 1 , wherein each social network of said one or more social networks are related to a different one of said content elements.