 In this paper, we propose a model called EPIC that combines utility-driven item adoption with the viral network effect helping to propagate adoption of and desire for items from users to their peers. We focus on the case of mutually complementary items and model their adoption behavior via supermodular value functions. We assume price is additive and use zero mean random noise to capture the uncertainty in our knowledge of user valuations. In this setting, we study a novel problem ofsocial welfare maximization : given item budgets, find an optimal allocation of items to seed nodes that maximizes the sum of expected utilities derived by users when the diffusion terminates .
<clarity>  In this paper, we propose a model called EPIC that combines utility-driven item adoption with the viral network effect helping to propagate adoption of and desire for items from users to their peers. We focus on the case of mutually complementary items and model their adoption behavior via supermodular value functions. We assume price is additive and use zero mean random noise to capture the uncertainty in our knowledge of user valuations. In this setting, we study a novel problem ofsocial welfare maximization : given item budgets, find an optimal allocation of items to seed nodes that maximizes the sum of expected utilities derived by users when the diffusion terminates .
 In this paper, we propose a model called EPIC that combines utility-driven item adoption with influence propagation over networks. Focusing on the mutually complementary setting, we study a novel problem ofsocial welfare maximization : given item budgets, find an optimal allocation of items to seed nodes that maximizes the sum of expected utilities derived by users when the diffusion terminates .