Optimizing Social Visibility in OSNs With Anonymity Guarantees: Efficient Algorithms and Applications

Online social network (OSN) is an ideal venue to enhance one's visibility. This paper considers how a user (called requester) in an OSN selects a small number of users and invites them as new friends/followers so as to maximize her “
social visibility
”. More importantly, the requester has to do this under the anonymity setting, which means she is not allowed to know the neighborhood information of other users in the OSN. In this paper, we first develop a mathematical model to quantify the social visibility and formulate the problem of visibility maximization with anonymity guarantee, abbreviated as “VisMAX-A”. We prove that the VisMAX-A problem is NP-hard even with an “perfect query oracle” which knows users’ neighborhood information. Then we design an algorithmic framework named as “AdaExp,” which adaptively expands the requester's visible set in multiple rounds. In each round of the expansion, the algorithmic framework uses a query oracle with anonymity guarantee to select one user to increase the requester's visibility. We prove the theoretical guarantees of our algorithmic framework, which quantify how the query oracle may influence the solution guarantee. By using probabilistic data structures like the k-minimum values (KMV) sketch and online learning methods like multi-armed bandit (MAB), we design an efficient query oracle with anonymity guarantees to estimate the best candidate to increase requester's visibility. We also conduct experiments on real-world social networks and validate the effectiveness of our algorithms. Lastly, we demonstrate applications of our algorithm on real-world data and show that one can increase her social visibility significantly by only adding a few (e.g., one or two) friends/followers in the OSNs.