The popularity of online social networks (OSNs) makes them attractive platforms to advertise products. Previous work on marketing in OSNs utilized older diffusion models that do not capture the interactions of modern OSNs and hence there is a need to develop a model that accounts for the interactions that occur in current OSNs. In this paper, we introduce a new model for information flow in online social networks that captures the sharing behavior exercised by users when they pass information from one online social network to their social circles in another network. We, then, formulate a problem of maximizing the marketing reach where the diversity of users’ other social networks is taken as a constraint. We also propose a greedy algorithm to solve the aforementioned optimization problem. Numerical results show that the proposed algorithm achieves better results than algorithms that are based on classical degree centrality metric and with comparable running time.
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