Suggesting (More) Friends Using the Implicit Social Graph
Abstract: Although users of online communication tools rarely
categorize their contacts into groups such as "family", "co-workers", or "jogging
buddies", they nonetheless implicitly cluster contacts, by virtue of their interactions
with them, forming implicit groups. In this paper, we describe the implicit social
graph which is formed by users' interactions with contacts and groups of contacts, and
which is distinct from explicit social graphs in which users explicitly add other
individuals as their "friends". We introduce an interaction-based metric for estimating
a user's affinity to his contacts and groups. We then describe a novel friend
suggestion algorithm that uses a user's implicit social graph to generate a friend
group, given a small seed set of contacts which the user has already labeled as
friends. We show experimental results that demonstrate the importance of both implicit
group relationships and interaction-based affinity ranking in suggesting friends.
Finally, we discuss two applications of the Friend Suggest algorithm that have been
released as Gmail features.