1. A computer-implemented method executed using one or more processors, the method comprising: receiving, by the one or more processors, a graph representing public social data comprising identity data and social link data, wherein the graph comprises nodes and directed edges, each edge connecting a pair of nodes, wherein each node represents an identity extracted from the public social data and each edge represents a social link extracted from the public social data from one identity to another different identity, wherein each node represents a distinct identity, and wherein each edge is a “me” edge if the edge represents a “me” social link between identities claimed by a link author as belonging to the same person or real-life entity, and a “friend” edge represents a “friend” social link between identities claimed by a link author as belonging to different persons or entities; and wherein each edge has a weight; quantifying, at the one or more processors, a connection strength between an ordered pair of nodes X and Y in the graph by determining: a distance, the distance being a smallest number of edges on any path from X to Y; a friend distance, the friend distance being a smallest number of friend edges on any path from X to Y; and an affinity score, the affinity score being a function of weights of edges along a path from X to Y; and determining, at the one or more processors, a total affinity between a source node S and a target node T as a sum of affinity scores along all possible paths of a length that does not exceed an upper limit K.
5. The method of claim 1 , wherein quantifying the connection strength between the ordered pair of nodes X and Y in the graph further comprises: determining an affinity score percentile, the affinity score percentile being the percentile of the affinity score within a list of all affinity scores attributed to X.