1Incentive Compatible Influence Maximization On Social Networks

Abstract—Information diffusion and influence maximization on social networks are well studied problems and various models and algorithms have been proposed. The main assumption in these studies is that the influence probabilities are known to the social planner. The influence probabilities can vary significantly with the type of the information and the time at which the information is recommended. Also there is no way to measure these probabilities from available data on social networks. The most accurate sources to obtain influence probabilities are the influencers themselves. In this report we formulate a game theoretic model of the information diffusion process so as to elicit influence probabilities truthfully from the agents. We present some preliminary results on applying mechanism design to the important problem of influence maximization in the context of information diffusion in social networks