Non-submodular model for group profit maximization problem in social networks

Abstract In social networks, there exist many kinds of groups in which people may have the same interests, hobbies, or political orientation. Sometimes, group decisions are made by simply majority, means that most users this reach an agreement, such as US Presidential Elections. A is called activated if $$\beta$$ β percent influenced group. Enterprise will gain income from all groups. Simultaneously, to propagate influence, enterprise needs pay advertisement diffusion cost. Group profit maximization (GPM) problem aims pick k seeds maximize expected considers benefit with GPM proved be NP-hard and objective function neither submodular nor supermodular. An upper bound a lower difference two functions designed. We propose submodular–modular algorithm (SMA) solve SMA shown converge local optimal. present randomized based on weighted coverage for apply sandwich framework get theoretical results. Our experiments verify efficiency our methods.