1. A non-transitory machine-readable medium which when executed by a data processing device to perform a method, the method comprising: receiving a search query from a user; retrieving a plurality of citations, wherein content from each of the plurality of citations matches the search query and the plurality of citations cites a plurality of objects; generating a subject list that includes a plurality of subjects, wherein each of the plurality of subjects are connected to the user either directly or indirectly in an influence network of a user; calculating an influence score for each of the plurality of subjects based at least on a distance on a path from the user to that subject in the influence network and each subject is a representation of a different user in the influence network; ranking the plurality of objects using a bias filter that includes a ranking function based on at least the influence scores of the subjects of each matching citation, wherein the influence scores are obtained from the user's subject list for those citing subjects that are on the list; and selecting a subset of objects from the ranked plurality of objects as the search results for presentation to the user.
1. A non-transitory machine-readable medium which when executed by a data processing device to perform a method, the method comprising: receiving a search query from a user; retrieving a plurality of citations, wherein content from each of the plurality of citations matches the search query and the plurality of citations cites a plurality of objects; generating a subject list that includes a plurality of subjects, wherein each of the plurality of subjects are connected to the user either directly or indirectly in an influence network of a user; calculating an influence score for each of the plurality of subjects based at least on a distance on a path from the user to that subject in the influence network and each subject is a representation of a different user in the influence network; ranking the plurality of objects using a bias filter that includes a ranking function based on at least the influence scores of the subjects of each matching citation, wherein the influence scores are obtained from the user's subject list for those citing subjects that are on the list; and selecting a subset of objects from the ranked plurality of objects as the search results for presentation to the user. 4. The machine-readable medium of claim 1 , wherein the method further comprises: creating the subject list by flattening the user's influence network of subjects up to a given number of degrees, levels, or depth.