6. The method of claim 2 , wherein the implicit bias of the first user comprises a field-based user bias that includes at least one biasing user node and at least one biasing-edge type, and wherein the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, further comprises: when the at least one first user attribute matches the at least one second user attribute: identifying the at least one biasing user node based on the at least one candidate user node for which the at least one first user attribute matches the at least one second user attribute, and identifying the at least one biasing-edge type based on at least one edge that connects the at least one candidate user node to at least one biased node of the social graph.
6. The method of claim 2 , wherein the implicit bias of the first user comprises a field-based user bias that includes at least one biasing user node and at least one biasing-edge type, and wherein the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, further comprises: when the at least one first user attribute matches the at least one second user attribute: identifying the at least one biasing user node based on the at least one candidate user node for which the at least one first user attribute matches the at least one second user attribute, and identifying the at least one biasing-edge type based on at least one edge that connects the at least one candidate user node to at least one biased node of the social graph. 7. The method of claim 6 , wherein the at least one biasing user node includes a copy of or a reference to the at least one candidate user node for which the at least one first user attribute matches the at least one second user attribute.