In this work it is our purpose to analyze and simulate a theoretical viral marketing context in a mathematical point of view. It is presented a mathematical formalization of the message affinity propagation model, which is a clustering algorithm used to cluster data points into multiple groups based on their similarity. This model is applied on Barabási-Albert social contact networks to analyze the choice of seed nodes between hubs and nodes with outstanding centrality measure values. Numerical studies are performed using a choice of parameters that describe situations of viral marketing diffusion.