Proactive pushing and caching has recently emerged as a promising technology to improve the quality of service in mobile networks. Given the fact that users' demand for content is largely driven by social networking, this paper combines the analysis of social networking with proactive pushing and caching by constructing a human-in-the-loop system model with a physical multicasting transmission. By taking social network structure, prediction and joint pushing and caching (JPC) into account, a closed-loop system is obtained, in which the input consists of arrivals of new content items, the control procedure is based on prediction and JPC, and the output is the cache-hit ratio (CHR). A prediction and JPC based adjustment algorithm is proposed to maximize the CHR of this system. It is shown that the prediction window, which refers to how far in the future predictions are made, and the prediction error have a significant impact on the performance of the system.