Abstract
Viral Marketing is a marketing technique that uses social network to get customers to market an idea, product, or service on their own by spreading the influence among their followers. The customers who are responsible of the information spreading are important and must be selected well. Therefore In this paper we will introduce models of seeding and diffusion in social networks and the application of these models in Viral Marketing. A seeding approach is introduced based on Cellular Learning Automata (CLAS) that will select the potential seed set that will start the Viral Marketing and will maximize the spread of influence in polynomial time and help the marketing campaign to reach and influence as many people as possible.