Stochastic Coupon Probing in Social Networks

TL;DR

This paper introduces a constant approximation policy for the stochastic coupon probing problem in social networks, optimizing influence under complex constraints with a novel adaptive approach.

Contribution

It presents the first constant approximation algorithm for stochastic coupon probing with monotone submodular utility functions under dual constraints.

Findings

Achieves maximum influence while satisfying inner and outer constraints.

Provides a constant approximation ratio for the problem.

Applicable to any monotone submodular utility function.

Abstract

In this paper, we study stochastic coupon probing problem in social networks. Assume there is a social network and a set of coupons. We can offer coupons to some users adaptively and those users who accept the offer will act as seeds and influence their friends in the social network. There are two constraints which are called the inner and outer constraints, respectively. The set of coupons redeemed by users must satisfy inner constraints, and the set of all probed users must satisfy outer constraints. One seeks to develop a coupon probing policy that achieves the maximum influence while satisfying both inner and outer constraints. Our main result is a constant approximation policy for the stochastic coupon probing problem for any monotone submodular utility function.