With the growing maturity of peer-to-peer (P2P) technology, IPTV (Internet protocol television) applications based on it have gained great commercial success, which has received more and more attentions from both global industry and academia. However, the characteristics of distribution, anonymity, rapid propagation, and large-scale users in P2P IPTV systems make them more likely to be vulnerable targets. In this paper, the procedure of content pollution attack in P2P IPTV systems is presented firstly, and then the various user behaviors under the pollution attack are analyzed. With that knowledge, a modeling framework with population dynamics of content pollution in P2P IPTV systems is proposed. Different from the existing content pollution propagation models, this model considers the impact of user behaviors in the content pollution attack of real world P2P IPTV systems, such as continuous watching behavior, arrival behavior, departure behavior. Theoretical analysis and simulation experiments show that the proposed model is a feasible and efficient tool to analyze the content pollution propagation in real world P2P IPTV systems, especially for the dynamic evolution of participating users and the user departure behavior.