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Traditional viral marketing problems aim at selecting a subset of seed usersfor one single product to maximize its awareness in social networks. However,in real scenarios, multiple products can be promoted in social networks at thesame time. At the product level, the relationships among these products can bequite intertwined, e.g., competing, complementary and independent. In thispaper, we will study the "interTwined Influence Maximization" (i.e., TIM)problem for one product that we target on in online social networks, wheremultiple other competing/complementary/independent products are being promotedsimultaneously. The TIM problem is very challenging to solve due to (1) fewexisting models can handle the intertwined diffusion procedure of multipleproducts concurrently, and (2) optimal seed user selection for the targetproduct may depend on other products' marketing strategies a lot. To addressthe TIM problem, a unified greedy framework TIER (interTwined InfluenceEstimatoR) is proposed in this paper. Extensive experiments conducted on fourdifferent types of real-world social networks demonstrate that TIER canoutperform all the comparison methods with significant advantages in solvingthe TIM problem.

Intertwined Viral Marketing through Online Social Networks