Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. Emails, Weblogs and Instant Messengers are popular instances of social networks. In this paper, the main target is having an advertisement according to user favorites and interests by mining his/her interactions in digital social networks. Briefly, in our method social network users are categorized based on the topic exchanges by them in the network, these topics discovered by mining of flowing data in that environment, considering that these topics shows the user willing, finally relevant advertisements will be represented to them. In fact, by finding people that have more chance to accept the desired advertisement, system will have more success over traditional method at lowered cost.