Suratna Budalakoti and Ron Bekkerman
In the 21st International World Wide Web Conference (WWW 2012)
We consider the problem of identifying the most respected, authoritative members of a large-scale online social network (OSN) by constructing a global ranked list of its members. The problem is distinct from the problem of identifying inﬂuencers: we are interested in identifying members who are inﬂuential in the real world, even when not necessarily so on the OSN. We focus on two sources for information about user authority: (a) invitations to connect, which are usually sent to people whom the inviter respects, and (b) members’ browsing behavior, as proﬁles of more important people are viewed more often than others’. We construct two directed graphs over the same set of nodes (representing member proﬁles): the invitation graph and the navigation graph respectively. We show that the standard PageRank algorithm, a baseline in web page ranking, is not eﬀective in people ranking, and develop a social capital based model, called the fair bets model, as a viable solution. We then propose a novel approach, called bimodal fair bets, for combining information from two (or more) endorsement graphs drawn from the same OSN, by simultaneously using the authority scores of nodes in one graph to inform the other, and vice versa, in a mutually reinforcing fashion. We evaluate the ranking results on the LinkedIn social network using this model, where members who have Wikipedia proﬁles are assumed to be authoritative. Experimental results show that our approach outperforms the baseline approach by a large margin.