  In this paper, we propose a new data based model for influence maximization
in online social networks. We use the theory of belief functions to overcome
the data imperfection problem. Besides, the proposed model searches to detect
influencer users that adopt a positive opinion about the product, the idea,
etc, to be propagated. Moreover, we present some experiments to show the
performance of our model.
